COMMunication
RESearch.NET

User Tools

Site Tools

You are here: index » theories_of_computer_mediated_communication_and_interpersonal_relations
Trace:
theories_of_computer_mediated_communication_and_interpersonal_relations

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Next revision		Previous revision
theories_of_computer_mediated_communication_and_interpersonal_relations [2017/04/17 09:54] – created hkimsciltheories_of_computer_mediated_communication_and_interpersonal_relations [2017/06/08 08:17] (current) – hkimscil
Line 1: Line 1:
-443 +See [[http://www.sagepub.com/upm-data/42241_14.pdf|Theories of Computer-Mediated Communication and Interpersonal Relations]]  
-CHAPTER 14 +{{:42241_14.pdf|Theories of Computer-Mediated Communication and Interpersonal Relations}} 
-Theories of ComputerMediated Communication +
-and Interpersonal Relations +
-Joseph B. Walther +
-Computer-mediated communication (CMC) +
-systems, in a variety of forms, have +
-become integral to the initiation, development, +
-and maintenance of interpersonal relationships. +
-They are involved in the subtle shaping +
-of communication in almost every relational +
-context. We may observe or participate in the +
-conversations of huge numbers of social actors, +
-from the Twitter messages of experts we have +
-never met to one’s family’s blog and from messaging +
-a barely acquainted Facebook friend to +
-coordinating with one’s spouse through texting +
-about who will pick up the kids that day or saying +
-via e-mail that one is sorry about the fight +
-they had that morning. Individuals exploit the +
-features of these media to make their best impression +
-and attract attention or to ward off undesired +
-contacts (Tong & Walther, 2011a). We +
-continually form and re-form our impressions +
-and evaluations of others online, from deciding +
-whose recommendations to trust in discussion +
-boards (Van Der Heide, 2008) to evaluating the +
-friend who portrays himself online in a not quite +
-accurate way (DeAndrea & Walther, in press). +
-Although many people perceive that social media +
-messages are trivial and banal, so is the stuff by +
-which relationships are maintained (Duck, Rutt, +
-Hurst, & Strejc, 1991; Tong & Walther, 2011b). +
-The ubiquity of CMC is not sufficient impetus +
-for it to be a focus of study in interpersonal communication +
-research. How CMC changes our +
-messages—how they are constructed, whether for +
-specific relational purposes or with lesser or +
-greater effect—remain important questions that +
-continue to drive inquiry in interpersonal CMC +
-research. How does the Internet affect the likelihood +
-of having relationships? With whom? And +
-how do we manage these relationships? How do +
-disclosures and affectations influence others and +
-ourselves, and how do online interpersonal processes +
-affect the instrumental and group dynamics +
-that technology enables? How do we exploit +
-existing technologies for relational purposes, and +
-how do we evade the potential dampening effects +
-that technologies otherwise may impose on +
-relational communication? How do technology  +
-444——PART IV: Processes and Functions +
-developers incorporate features into communication +
-systems specifically designed to support and +
-enhance relational functions? +
-There are many methodologies employed in +
-studying CMC and social interaction. Large-scale, +
-sophisticated surveys enumerate what people are +
-doing online and why they say they are doing +
-them (e.g., Katz & Rice, 2002; the Pew Internet & +
-American Life Project at http://pewinternet.org/). +
-There are accounts of the metaphors that define +
-the online experience for Internet date seekers +
-(e.g., Heino, Ellison, & Gibbs, 2010) and interpretive +
-investigators’ insights from interacting with +
-groups of young people about what is going on +
-and what it means online (boyd, 2007). Conference +
-proceedings from design experiments report cognitive +
-and affective responses to variations in the +
-representation of others’ online behaviors or different +
-interface characteristics with which to +
-behave online (e.g., the ACM Digital Library +
-at http://portal.acm.org/dl.cfm). A number of +
-recent and forthcoming volumes address different +
-aspects of interpersonal interaction online, +
-including works by Amichai-Hamburger (2005), +
-Baym (2010), Joinson, McKenna, Postmes, and +
-Reips (2007), Konijn, Utz, Tanis, and Barnes +
-(2008), Papacharissi (2010), Whitty and Carr +
-(2006), and Wright and Webb (2011), among others. +
-Any of these approaches provide glimpses +
-into the changing landscape of interpersonal +
-communication and CMC. No one chapter can +
-paint this landscape or summarize it well. Worse +
-yet, such an amalgamation of facts would suffer +
-from a lack of coherence, reflecting a field with +
-more work being done than consensus on what +
-work should be done. Moreover, to describe what +
-people are doing interpersonally with CMC today +
-would be to invite obsolescence very quickly, +
-given the pace of change in communication and +
-technology. Readers who expect such an accounting +
-in this essay will be disappointed. +
-Alternatively, despite the field’s youth, there +
-are now a greater number of theoretical positions +
-directly related to CMC than any single overview +
-of the field has previously described. Some theories +
-have matured and are due for evaluation, +
-both in light of a number of empirical tests of +
-their validity, and intensions and extensions of +
-their explanatory power. New technological +
-developments may have enlarged or diminished +
-their relative scope. Newer theories have also +
-arisen, some barely tested, the ultimate utility of +
-which remains to be seen. This is not to suggest +
-that the only theories the field needs are those +
-focusing specifically on CMC. As Yzer and +
-Southwell (2008) suggested, the most useful +
-explanations of CMC may be those that rest +
-strongly on robust theories developed in traditional +
-contexts. For the present purposes, the +
-chapter focuses on CMC-specific theoretical formulations. +
-As Scott (2009) observed, “We can’t +
-keep up with new innovations, so we need theory +
-and models that can” (p. 754). +
-This chapter provides, first, a description and +
-evaluation of 13 major and minor theories of +
-CMC. Although readers may find many of these +
-approaches reviewed in other sources, particular +
-efforts have been made to review the theories’ +
-development and status since the publication of +
-the previous edition of this Handbook (see +
-Walther & Parks, 2002). These theories are classified +
-according to their conceptualization of the +
-way users respond to the characteristics of CMC +
-systems, particularly in the adaptation to cue +
-systems that differ from face-to-face communication. +
-These theories include the now standard +
-classification of cues-filtered-out theories, which +
-assert that systematic reductions in the nonverbal +
-cues conveyed by different communication systems +
-lead to impersonal orientations among +
-users. There are differences among the foci of +
-impersonal orientations, some of which are asocial +
-and others quite specific and social in nature. +
-The second group of theories depicts how characteristics +
-of communicators, their interactions +
-with others, and contextual factors affect the +
-perceived capacities of different communication +
-systems. These perceptions, in turn, affect the +
-expressiveness and normative uses of these same +
-technologies as if the capacities themselves had +
-changed. The next set of theories reflects the +
-ways in which communicators adapt to or exploit  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——445 +
-the cue limitations of CMC systems to achieve or +
-surpass face-to-face levels of affinity. Finally, new +
-theoretical ideas are mentioned that address the +
-utility of different media over the progression of +
-usage sequences or relational stages or compare +
-media effects of different kinds based on the relative +
-effortfulness of different channels. The discussion +
-includes numerous examples from +
-research that help exemplify critical findings +
-related to these frameworks. +
-The chapter ends with a few notes of concern +
-about trends in contemporary CMC research. +
-These trends represent understandable developments +
-given the nature of the field, yet they also +
-present potential problems in the further development +
-of knowledge in certain domains. These +
-concerns involve the role of face-to-face comparisons +
-in technology-focused research, the +
-potential impact of new technologies on earlier +
-CMC theories, and the implications of multimodality +
-in relationships (i.e., how to learn about +
-the usage of a variety of communication systems +
-within any single relationship). +
-Cues-Filtered-Out Theories +
-As numerous reviews have reflected, Culnan and +
-Markus (1987) coined the term cues-filtered-out +
-to describe a group of theories sharing the premise +
-that CMC has no nonverbal cues and therefore +
-occludes the accomplishment of social +
-functions that typically involve those cues. +
-Social Presence Theory +
-Social presence theory was imported from teleconferencing +
-research as one of the first analytic +
-frameworks applied to CMC. Short, Williams, +
-and Christie’s (1976) theory argued that various +
-communication media differed in their capacity +
-to transmit classes of nonverbal communication +
-in addition to verbal content. The fewer the +
-number of cue systems a system supported, the +
-less warmth and involvement users experienced +
-with one another. Hiltz, Johnson, and Agle (1978) +
-and Rice and Case (1983) first applied this model +
-to CMC, using it to predict that CMC rendered +
-less socio-emotional content than other, multimodal +
-forms of communication. Numerous experiments +
-supported these contentions. Nevertheless, +
-a number of theoretical and methodological +
-critiques by other researchers challenged the +
-social presence explanation of CMC dynamics +
-(e.g., Lea & Spears, 1992; Walther, 1992). These +
-critiques challenged several assumptions of the +
-social presence model and identified artifacts in +
-the research protocols that supported its application +
-to CMC. +
-Despite the demise of social presence in some +
-quarters of CMC research, extensive research +
-and definition efforts have continued with +
-respect to the role of presence with regard to settings +
-such as virtual reality and computer-based +
-gaming. Biocca, Harms, and Burgoon (2003) +
-suggested definitional issues that a robust theory +
-of social presence might require and the prospective +
-benefits of a renewed social presence +
-theory for comparing effects among various +
-media. K. M. Lee (2004) highlighted the various +
-conceptions of presence in related literatures, +
-including telepresence, copresence, and social +
-presence, as each construct describes somewhat +
-different states of awareness of the self and others +
-during electronic communication (see also +
-Lombard & Ditton, 1997). Nevertheless, the +
-various constructs and related measures are +
-often used interchangeably or in duplication. +
-Nowak and Biocca’s (2003) experiment on the +
-optimal level of anthropomorphism for avatars, +
-for example, compared the research participants’ +
-responses to lifelike, cartoonish, or abstract avatars +
-on measures of presence, copresence, and +
-social presence. Each of the presence variables +
-reflected the same result: Abstract rather than +
-lifelike avatars stimulated the greatest presence +
-responses. +
-Although researchers have in large part +
-rejected the notion that CMC is inherently inferior +
-to traditional communication media on outcomes +
-such as social presence, there appears to be +
-a resurgence of presence-related evaluations that  +
-446——PART IV: Processes and Functions +
-that were common in first-generation CMC (i.e., +
-text-based e-mail, chat, and discussions) being +
-applied to next-generation CMC, which features +
-photos, graphics, avatars, or videos. Many individuals +
-apparently assume that we no longer +
-need to concern ourselves with earlier forms of +
-minimal-cue CMC (or research about them) +
-now that we have systems with greater bandwidth +
-and presence. Education technologists, in +
-particular, have been eager to recommend avatarbased +
-interactions in Second Life as a cure for +
-what remains, in the view of many, an impoverished +
-level of social presence in plain-text educational +
-conferencing (see Baker, Wentz, & Woods, +
-2009; Barnes, 2009; Childress & Braswell, 2006; +
-Gunawardena, 2004), without much evidence of +
-avatars’ interpersonal impact beyond what may +
-be expected due to novelty or to the hyperpersonal +
-intercultural potential of asynchronous +
-learning networks (e.g., Oren, Mioduser, & +
-Nachmias, 2002). In a world where we know our +
-communication partners by photo if not by face, +
-plain-text CMC with no additional multimedia +
-is, in some corners, being retro-conceptualized as +
-never having been quite good enough, especially +
-in comparison with the more presence-bearing +
-media that seem (for now) to be here to stay. It +
-appears that, although the formal theory of social +
-presence has become disregarded in many quarters +
-of CMC research, the concept of social presence +
-as an inherent consequence of multiple cues +
-remains alive and well (e.g., Bente, Rüggenberg, +
-Krämer, & Eschenburg, 2008). +
-It remains to be seen whether social presence +
-or some other construct and framework will +
-emerge to account for why individuals use various +
-new media for various relational activities. +
-Observers of the new multimodal world of relationships +
-have yet to identify coherent explanations +
-about the relational functions and goals to +
-which older new media and newer new media +
-are being strategically applied. Meanwhile, +
-plain-text messaging through e-mail, mobile +
-phones, and the 140-character Twitter tweet +
-suggest that text-based CMC is not at all gone. +
-The subject of multiple media, interpersonal +
-functions, and sequences is discussed once more +
-at the end of this chapter. +
-Lack of Social Context Cues +
-Like social presence theory, the lack of social +
-context cues hypothesis (Siegel, Dubrovsky, +
-Kiesler, & Mcguire, 1986; Sproull & Kiesler, 1986) +
-once guided numerous studies on the interpersonal +
-and group impacts of CMC, although it has +
-been more or less set aside in response to contradictions +
-that became apparent in native Internet +
-environments (see Sproull & Faraj, 1997), as well +
-as to formal theoretical and empirical challenges. +
-The framework originally specified that CMC +
-occluded the cues to individuality and normative +
-behavior that face-to-face interaction transacts +
-nonverbally. As a result, according to the model, +
-CMC users became deindividuated and normless; +
-CMC prevented users from attuning to others’ +
-individual characteristics, such as charisma, +
-dominance, or affection, resulting in a cognitive +
-reorientation of its users. The lack of nonverbal +
-cues led them to become self-focused and resistant +
-to influence, disinhibited, belligerent, and +
-affectively negative. +
-As with social presence theory, a number of +
-critical issues related to the research paradigms +
-accompanying the lack of social context cues +
-approach, and to the various theoretical issues it +
-raised, have led to the model’s retreat. Negative +
-social responses to CMC have been accounted for +
-theoretically through more complex frameworks +
-that can explain both negative affective outcomes +
-as well as positive ones, in formulations +
-incorporating CMC’s impersonal, interpersonal, +
-and hyperpersonal effects (see Walther, 1996). +
-Researchers articulated alternative assumptions +
-and employed different research designs, leading +
-to the development of second-generation theories +
-of CMC. These latter positions predict different +
-social and interpersonal effects of CMC +
-media depending on other contextual factors +
-(Walther, 2010). +
-That said, research still surfaces that shares the +
-basic premises of the lack of social context cues  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——447 +
-hypothesis, and such studies, ironically, often +
-include methodological strategies that were criticized +
-with regard to the original research on the +
-lack of social context cues and social presence +
-models. One such approach has appeared in several +
-experiments on compliance gaining and +
-social influence in CMC (e.g., Guadagno & +
-Cialdini, 2002): The absence of nonverbal cues in +
-CMC is said to prevent communicators from +
-detecting demographic, personality, and interpersonal +
-characteristics of others. The implication +
-in this case is that CMC confers no peripheral +
-cues to persuasion (see Petty & Cacioppo, 1986). +
-As a result, it is suggested, CMC users process +
-messages based on argument strength—that is, +
-through central routes to persuasion alone—and +
-they experience less overall attitude change than +
-do off-line communicators. Methodologically, +
-such research has employed very short interaction +
-sessions among strangers in CMC and faceto-face +
-(e.g., Di Blasio & Milani, 2008), an +
-approach that has been demonstrated elsewhere +
-to impose a time-by-medium interaction effect, +
-artifactually dampening impression formation in +
-CMC (for a review, see Walther, 1992, 1996). +
-Other persuasion research following a lack +
-of social context cues approach apparently +
-employed short, scripted real-time chat sessions +
-as the operationalization of e-mail yet made +
-claims about e-mail’s persuasion-related potential +
-on that platform (Guadagno & Cialdini, +
-2007). Whereas gender-by-medium differences +
-in persuadability are obtained in such research, it +
-is difficult to know how to generalize these findings. +
-Using synchronous CMC chat to describe +
-asynchronous e-mail is a questionable, although +
-certainly not a novel, approach. This conflation +
-should be of concern, although differences due to +
-synchronous versus asynchronous CMC remain +
-understudied in CMC research. +
-In a similar vein, Epley and Kruger (2005) +
-argued that e-mail’s lack of nonverbal cues prevents +
-users from deciphering others’ individual +
-characteristics following the presentation of a +
-false pre-interaction expectancy about a pending +
-conversational partner. The authors conducted +
-several experiments in which they primed interviewers +
-to expect a high or low level of intelligence +
-or extraversion from an interviewee. Some +
-dyads communicated using a voice-based system, +
-while so-called e-mail communicators used a +
-real-time CMC chat system. In the voice conditions, +
-although conversations were restricted to +
-simple, predetermined questions and spontaneous +
-answers, they constituted actual interactions +
-between two real (randomly assigned) persons. +
-In contrast, there was no real interaction between +
-CMC interviewers and their ostensible interviewees, +
-since the responses interviewers received +
-to their questions were sent by a researcher who +
-had transcribed what a voice-based interviewee +
-had said to a different, voice-based interviewer. +
-This research strategy was intended to prevent +
-the introduction of random variations in CMC +
-users’ language in order to provide a true test of +
-the difference between CMC and speech. Epley +
-and Kruger found that expectancies persisted in +
-the post-CMC evaluations of partners, although +
-they dissipated in voice. +
-A replication of this work by Walther, +
-DeAndrea, and Tong (2010) challenged the former +
-study’s methods, particularly the use of +
-transcribed speech as the operationalization of +
-CMC interviewee responses. This concern +
-focused on the lack of real interactions in the +
-prior study and the employment of language that +
-had been generated accompanying voice, in +
-speech, as if it was structurally and functionally +
-identical to the language that is generated in +
-spontaneous CMC, where communicators know +
-that there are no vocal cues to convey identity +
-and social meanings. Walther, DeAndrea, and +
-Tong argued that CMC users adapt to the +
-medium by altering their language in a way that +
-compensates for the absence of nonverbal cues. +
-Their study therefore involved bona fide interviewees +
-in both voice and CMC who could generate +
-naturalistic responses to interviewers in +
-both media. CMC users’ postdiscussion impressions +
-were rated as more intelligent than those of +
-voice-based partners, in contrast to Epley and +
-Kruger’s (2005) findings and consistent with the  +
-448——PART IV: Processes and Functions +
-hyperpersonal model of CMC (Walther, 1996). +
-Impressions changed in conjunction with the +
-number of utterances exchanged, consistent with +
-the social information processing theory of CMC +
-(Walther, 1992). +
-Indeed, the history of contradictions between +
-cues-filtered-out findings and the more prosocial +
-effects of CMC can be explained in part by the +
-methodological constraints on CMC interaction, +
-which reflect competing theoretical orientations +
-about communication and CMC (Fulk & Gould, +
-2009; Walther, 2010). +
-Media Richness +
-Media richness theory (Daft & Lengel, 1986), +
-also known as information richness theory (Daft +
-& Lengel, 1984), originally modeled the relative +
-efficiency of different communication media for +
-reducing equivocality in organizational decision +
-making. It has also been applied to interpersonal +
-situations either formally or informally. The +
-term rich media is often used casually in the +
-literature to signify multimodal or greaterbandwidth +
-media, that is, communication media +
-that support multiple verbal and nonverbal cue +
-systems. +
-Media richness theory seems to be one of the +
-most popular models of CMC (for a review, see +
-D’Urso & Rains, 2008). This may be because some +
-of its core constructs are so intuitively appealing, +
-especially the media richness construct. This construct, +
-in turn, is defined theoretically by four +
-subdimensions: (1) the number of cue systems +
-supported by a medium, (2) the immediacy of +
-feedback provided by a medium (from unidirectional +
-to asynchronously bidirectional to simultaneous +
-bidirectional interaction), (3) the potential +
-for natural language (compared with the more +
-formal genre of memoranda, business letters, or +
-data printouts), and (4) message personalization +
-(i.e., the degree to which a message can be made +
-to address a specific individual). So in the original +
-formulation, face-to-face communication is the +
-richest mode because it includes multiple-cue +
-systems, simultaneous sender-and-receiver +
-exchanges (providing great immediacy of feedback), +
-natural language, and message personalization. +
-Telephones, letters, and memoranda each +
-offer progressively declining levels of richness. +
-The second core construct of the model is the +
-equivocality of a messaging situation. Equivocality +
-is defined as the degree to which a decisionmaking +
-situation and information related to it are +
-subject to multiple interpretations. +
-The theory argues that there is a match +
-between the equivocality of a message situation +
-and the richness of the medium with which to +
-address it: To be most efficient, greater equivocality +
-requires more media richness, and lesser +
-equivocality requires leaner media. Although the +
-theory was originally formulated so that the result +
-of optimal match (or of mismatch) affects efficiency, +
-it is often described in the literature as +
-being related to communication effectiveness. +
-It is somewhat surprising that the theory +
-remains as frequently employed as it does given +
-that, even within the domain of organizational +
-communication, it has a poor history of empirical +
-support. The first empirical investigation of the +
-theory (Daft, Lengel, & Trevino, 1987) addressed +
-it indirectly by asking managers to indicate in a +
-questionnaire what media they would use to +
-address a list of various communication situations. +
-These situations had been rated by other +
-research participants in terms of their equivocality. +
-The degree to which the test managers’ media +
-selections (in terms of richness) matched the situations’ +
-equivocality led to a media sensitivity score +
-for each manager. Through inspection of the +
-same managers’ personnel evaluations, researchers +
-found a correlation between media sensitivity +
-and managerial performance. These results were +
-interpreted as supporting the theory. +
-One can see that the investigation described +
-above does not actually test the theoretical relationships +
-specified by the theory; rather, it evaluates +
-peripheral processes and implications that +
-may be related to the model less directly. That is, +
-rather than examining direct relationships +
-between the actual use of differently rich media, +
-equivocal message situations, and efficiency  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——449 +
-(e.g., the time and effort required), Daft et al. +
-(1987) examined organizationally related implications +
-of managers’ projections of media selection. +
-Such findings have been contested by other +
-researchers in a variety of ways. For example, +
-Markus (1994) questions whether the projective, +
-self-report approach to asking managers what +
-media they would choose for various communication +
-tasks generalizes to managers’ actual +
-media use. In her own study, Markus found that +
-managers express media selection preferences +
-very consistent with the matches prescribed by +
-Daft and Lengel (1986) when completing questionnaires. +
-By shadowing several managers, however, +
-Markus found that their media selection +
-behavior frequently departed from their questionnaire +
-responses. It appears that managers +
-hold normative beliefs about media choice that +
-align with the media richness model but the normal +
-constraints and spontaneous-communication +
-needs that they face lead them to select +
-media in ways that defy media richness sensibilities, +
-and according to Markus, they do not suffer +
-any decrement in performance as a result. +
-A second significant threat to the model came +
-in the form of an experiment by Dennis and +
-Kinney (1998) that sought to test directly the +
-core theoretical dynamics of media richness theory +
-as well as its extension toward interpersonal +
-perceptions of online collaborators. This study +
-involved small groups that addressed a simple or +
-equivocal task, using videoconferencing (greater +
-in richness) or text-based messaging (lower in +
-richness). They found that media richness produced +
-differences in the time it took different +
-groups to complete their tasks. Media richness +
-did not, however, interact with task equivocality +
-to affect decision quality or interpersonal perceptions. +
-More recent work examined media richness +
-variations with differences in high-context +
-versus low-context cultural backgrounds of users +
-(Setlock, Quinones, & Fussell, 2007). Researchers +
-predicted that there would be more benefit from +
-using videoconferencing than from a reducedbandwidth +
-medium among those from a highcontext +
-culture (see Hall, 1976). Culture, however, +
-did not interact with media richness differences +
-on conversational efficiency, task performance, +
-or satisfaction. +
-Walther and Parks (2002) criticized the model +
-as being unable to generate hypotheses that apply +
-to many forms of CMC. Their concern focused +
-on the four subdimensions of richness. When +
-applying these criteria to traditional media, it is +
-easy to see that all four dimensions tend to vary in +
-conjunction with one another as one compares +
-media. As one moves away from face-to-face to +
-memoranda, for example, there are fewer code +
-systems, less immediacy of feedback, less natural +
-language, and little message personalization. +
-However, e-mail does not fit into this scheme so +
-neatly. Although e-mail is generally text based and +
-therefore low in multiple codes, it may be +
-exchanged relatively rapidly (if all addressees are +
-online at the same time), it may use natural language +
-(or formal language), and its capacity for +
-message personalization is great. Likewise, one +
-may use Facebook to broadcast information +
-about oneself to a large audience, but Facebook +
-also features public displays of relatively private +
-one-to-one messages between friends that are +
-sometimes very personally, even idiosyncratically, +
-encoded. As these examples should make clear, +
-media richness theory offers no clear method for +
-ascribing a unitary richness value when the +
-underlying criteria that constitute richness may +
-reflect very different values, and researchers cannot +
-apply the model to media that offer so much +
-variation among richness characteristics. This +
-issue may be an underlying factor that has contributed +
-to the troubling level of empirical support +
-for the model in CMC research. +
-Notwithstanding the troubling level of empirical +
-support, media richness theory continues to +
-be applied to new media and new interpersonal +
-settings (without much success). For instance, +
-Cummings, Lee, and Kraut (2006) used media +
-richness theory to predict that friends from high +
-school use telephone and face-to-face contact +
-more frequently than CMC to maintain their +
-friendships when they transition to college. Their +
-results showed, however, that CMC was the most  +
-450——PART IV: Processes and Functions +
-frequently used medium among such friends. +
-Rather than abandon the media richness framework, +
-the authors conjectured that the relatively +
-greater expense of making long-distance phone +
-calls interfered with their predictions. +
-In a different vein, Hancock, Thom-Santelli, +
-and Ritchie (2004) used media richness theory +
-in a study comparing individuals’ media preferences +
-for deceiving another person. They argued +
-that lying can be considered an equivocal message, +
-and therefore, individuals should select +
-rich media such as face-to-face or telephone for +
-deception more often than they would choose +
-text-based chat or e-mail. Results of a diary +
-study did not support the hypothesis. Telephone +
-was the most frequently used medium for +
-deception, followed by face-to-face and instant +
-messaging (which did not differ from each +
-other), and e-mail was the least frequently used +
-medium for deception. Hancock et al. (2004) +
-concluded with a features-based explanation of +
-their findings: Individuals resist the use of +
-media that are recordable (such as CMC) so +
-that their lies cannot be caught later or provide +
-evidence with which to hold them to account. +
-The recordability characteristic of new media, +
-they argued, questions the applicability of +
-media richness’s assumption that communication +
-channels differ along a single dimension. +
-Interestingly, more recent research identifying +
-an abundance of deception in date-finding websites +
-has yet to be reconciled with this study’s +
-conclusion that liars avoid recordable and +
-accountable media. +
-The Social Identity Model of +
-Deindividuation Effects +
-The social identity model of deindividuation +
-effects, or SIDE model, has had an interesting evolution +
-in the literature. Although its developers +
-have argued that it is decidedly not about interpersonal +
-communication, at least in terms of the +
-mechanisms that generate its predictions (e.g., +
-Postmes & Baym, 2005), it has been applied to +
-many settings that appear to be interpersonal in +
-nature. At one point, SIDE was one of the most +
-dominant theories of CMC. Changes to the theory +
-in response to empirical challenges and changes in +
-communication technology—attributes that bear +
-on the theory’s central assumptions—appear to +
-have accompanied a marginal decline in its popularity +
-and scope. In certain contexts, however, it +
-remains a most parsimonious and robust explanatory +
-framework for CMC dynamics. +
-The SIDE model is included here as a cuesfiltered-out +
-theory because it, like others, considers +
-the absence of nonverbal cues in CMC as +
-an impersonalizing deterrent to the expression +
-and detection of individuality and the development +
-of interpersonal relations online. The +
-SIDE model differs from other cues-filtered-out +
-approaches, however, in that rather than leave +
-users with no basis for impressions or relations +
-at all, it predicts that CMC shifts users toward a +
-different form of social relations based on social +
-self-categorization. The SIDE model (Lea & +
-Spears, 1992; Reicher, Spears, & Postmes, 1995) +
-specifies two factors that drive online behavior. +
-The first factor is the visual anonymity that +
-occurs when CMC users send messages to one +
-another through text (in real-time chat or in +
-asynchronous conferencing and e-mail). When +
-communicators cannot see each other, the model +
-puts forth, communicators do not attune themselves +
-to one another on the basis of their interindividual +
-differences. Drawing on principles of +
-social identification and self-categorization theories +
-(Tajfel, 1978; Tajfel & Turner, 1979), the +
-model originally argued that visual anonymity +
-led to deindividuation, or a loss of awareness +
-with regard to one’s own (and others’) individuality. +
-When in such a state of deindividuation, +
-the second major factor in the theory comes into +
-play: whether CMC users orient themselves to +
-some salient social category or group (i.e., a +
-social identification). If a CMC user experiences +
-a social identification, the user will relate to +
-other CMC users on the basis of in-group (or +
-out-group) dynamics. These classifications then +
-drive users’ perceptions of similarity and attraction +
-toward online partners in gross terms, that  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——451 +
-is, as a unified perception based on of whether +
-others online seem to belong to the same group +
-that is salient to the user, rather than as a sum or +
-average of one’s perceptions of each other partner +
-in a conversation. +
-The model also specified, theoretically, that +
-when a deindividuated CMC user orients to an +
-individualistic identification rather than a social +
-identification, then systematic effects on similarity +
-and attraction should not occur. The model +
-views interpersonal (rather than group) attraction +
-toward other members as an aggregation of +
-randomly distributed values based on a person’s +
-attraction to each idiosyncratic individual. That +
-is, when perceiving others individually, one may +
-like one person a lot, dislike another person a lot, +
-and like others to different degrees, which, on +
-balance, should average to some neutral level. +
-Attraction to a group to which one belongs, in +
-contrast, should be systematically positive. This +
-difference in the form of attraction marks a key +
-distinction between a group-based and an interpersonally +
-based approach to the social dynamics +
-of CMC (Lea, Spears, & de Groot, 2001; for a +
-review, see Walther & Carr, 2010). +
-The most basic research strategy that provided +
-evidence for SIDE involved experiments manipulating +
-the two factors, visual anonymity and type +
-of identification. In a prototypical experiment, +
-one half of the small groups of CMC users in +
-an experiment would communicate with one +
-another using a text-based chat system only, +
-whereas the other half would use the chat system +
-and be shown photos that were supposed to represent +
-the members. The former condition provides +
-visual anonymity, presumably instigating +
-deindividuation, whereas the latter condition +
-involves visual identification and individuation. +
-The second factor, group identification, is manipulated +
-by prompting participants explicitly to +
-look for the unique and distinctive characteristics +
-of the group in which they were involved rather +
-than to try to detect what made the individuals +
-with whom they were conversing unique and +
-different from one another. Such research has +
-produced predicted interaction effects of visual +
-anonymity/identifiability by group/interpersonal +
-identity, with conditions involving both visual anonymity +
-and group identity providing the greatest +
-scores on attraction (e.g., Lea & Spears, 1992). +
-The SIDE model’s advocates originally argued +
-that the nature of group memberships with +
-which CMC users identified comprised fairly +
-general social categories (e.g., English vs. Dutch +
-nationalities, psychology vs. business majors, +
-men vs. women, etc.). Although attempts to +
-arouse these kinds of identifications have been +
-employed in SIDE experiments, they have not +
-produced effects as clearly as when identification +
-was targeted only with the local group, that is, the +
-unique and specific small group involved in the +
-interaction. These results have led to revisions of +
-the SIDE model, and recent versions focus on +
-visually anonymous CMC leading to in-group +
-identification with the group of participants +
-rather than via larger social categories. +
-Although the SIDE model is distinctively not +
-about an interpersonal basis for online relations, +
-it has been argued to offer an explanatory framework +
-for what others consider to be interpersonal +
-phenomena. Lea and Spears (1995) argued +
-that SIDE can explain the development of +
-romantic relationships online. Rejecting notions +
-that intimate attraction is necessarily and exclusively +
-premised on physical appearance or the +
-exchange of nonverbal cues (a rejection with +
-which several other CMC theories in this chapter, +
-described below, concur), they argued that intimacy +
-may result from the perceptions of similarity +
-that arise from a couple’s shared membership +
-in a variety of social categories (see also Sanders, +
-1997). From this perceptive, although partners +
-who communicate romantically online may +
-believe that they love each other interpersonally, +
-this would be an illusion. Their projection of +
-interpersonal intimacy would be an outgrowth +
-and projection of the similarity/attraction they +
-share on the basis of their social (rather than +
-interpersonal) identifications. Other essays have +
-made quite strident pronouncements about the +
-superiority of a groups-based, rather than an +
-interpersonally-based, approach to understanding  +
-452——PART IV: Processes and Functions +
-a variety of online social responses. They have +
-gone so far as to suggest that interpersonally +
-based explanations for systematic social effects in +
-online behavior are empirically conflicting and +
-conceptually misleading and that they have +
-impeded theoretical understanding about CMC +
-effects (Postmes & Baym, 2005). +
-Despite these pronouncements about its overarching +
-superiority as an organizing model for +
-the entire field, the SIDE model seems now to be +
-taking a more appropriately limited place in +
-CMC research. This change appears to be due to +
-uncertainties about the components of the model +
-itself, empirical “competitions” in which social +
-and interpersonal components both appear, and +
-new media forms that alternately extend or +
-restrict the scope of SIDE’s domain. +
-The deindividuation aspect of the model itself +
-has been redefined (see E.-J. Lee, 2004). Although +
-visual anonymity is still a key predictor of SIDE’s +
-effects, empirical studies have led to questions +
-about the deindividuation that anonymity was +
-said to produce, in terms of its actual potency +
-and its theoretical necessity in the model. +
-Research has found that in some cases SIDE-like +
-responses to an anonymous online crowd are +
-greater when a CMC user is more, rather than +
-less, self-aware (Douglas & McGarty, 2001). This +
-and other studies have led SIDE theorists to +
-argue that it is not deindividuation but rather +
-depersonalization—the inability to tell who is +
-who online—that is (and always has been) the +
-construct on which SIDE phenomena depend. It +
-is admirable that the theory is open to such +
-modification, although it represents a significant +
-departure from the important elements of social +
-identity theory on which it originally drew and +
-from assertions that were argued strongly in earlier +
-articulations of the model. +
-Responding in part to SIDE advocates’ claims +
-that their model could explain seemingly interpersonal +
-effects, researchers made efforts to +
-demonstrate more carefully whether group or +
-interpersonal factors were operating in their +
-CMC studies. Greater attention has been paid to +
-whether the operationalizations and measurements +
-involved in research can discern group-based +
-constructs from interpersonally based constructs +
-(Wang, 2007). Moreover, experiments have directly +
-compared SIDE-based versus interpersonallybased +
-factors in the same study for their effects +
-on the responses of CMC groups. Rogers and +
-Lea (2004), for example, studied a number of +
-virtual groups composed of students in England +
-and the Netherlands who worked over an +
-extended period of time via asynchronous conferencing +
-and real-time chat. Steps were employed +
-to maximize the salience of each virtual group’s +
-unique identity (i.e., researchers addressed groups +
-by their collective name only, rather than individually +
-by member). Repeated measures indicated +
-that group attraction did not maintain +
-evenly or increase over time. To the contrary, +
-interpersonal affiliation among members reflected +
-marginal increases over the duration of the +
-groups’ experience. More recently, Wang, Walther, +
-and Hancock’s (2009) experiment with visually +
-anonymous online groups involved a SIDE-based +
-assignment of four members to two distinct subgroups. +
-The researchers further prompted one +
-member of each four-person group to enact +
-interpersonally friendly (or unfriendly) behaviors +
-toward the rest of the members. In general, other +
-members evaluated the deviants in each group on +
-the basis of the individuals’ interpersonal behaviors +
-and not on the basis of those individuals’ ingroup +
-or out-group status with respect to other +
-subgroup members. These results suggest that +
-SIDE is less robust than previously suggested +
-when CMC users confront bona fide behavioral +
-differences among members while remaining +
-visually anonymous. A recent essay offers a more +
-tempered view of when SIDE and other intergroup +
-dynamics are likely to arise in CMC and +
-when they give way to interpersonal dynamics +
-(Walther & Carr, 2010). +
-Recent revisions to the SIDE model have also +
-retracted its previous assertions that visually +
-anonymous CMC users cannot, theoretically, +
-relate to one another as individuals (Postmes, +
-Baray, Haslam, Morton, & Swaab, 2006; Postmes, +
-Spears, Lee, & Novak, 2005). Now individuals are  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——453 +
-seen, over time and under conditions of visual +
-anonymity, to form relationships with each other +
-first and then to identify with and form attachments +
-to the small, interacting group. Group +
-identification arises inductively in this new perspective. +
-These formulations represent a major +
-departure from SIDE’s previous assumptions. +
-They also leave unaddressed the mechanisms by +
-which interacting individuals online become sufficiently +
-attracted to one another to provide the +
-interpersonal motivation, attraction, and reward +
-that may be required to facilitate the durations of +
-interaction required for individuals to develop an +
-emergent group identity. +
-New media forms also raise interesting issues +
-with regard to SIDE’s scope. Many new technologies +
-seem quite amenable to SIDE analysis of +
-their effects on users, while others seem distinctly +
-out of its reach. Communication systems such as +
-social network sites, which confront CMC users +
-with photos of prospective interactants, resemble +
-the control group conditions in the prototypical +
-SIDE experiment, that is, the visually identified +
-conditions for which SIDE predicts no systematic +
-effects. Alternatively, some new Web-based communication +
-systems are very compatible with +
-SIDE dynamics (see Walther, 2009): CMC systems +
-display anonymous comments with no +
-visual identification of other commenters, no +
-interaction with other commenters, and the relatively +
-clear implication that participants belong +
-to the same social group. A recent study drew on +
-SIDE theory successfully to predict readers’ +
-responses to the comments apparently left by +
-other YouTube viewers in reaction to antimarijuana +
-public service announcements. Researchers +
-appended experimentally created comment sets +
-(featuring all-positive or all-negative comments) +
-to institutionally produced antimarijuana videos +
-on YouTube pages. The more the participants +
-identified with the ostensible commenters, the +
-more the valence of those comments affected viewers’ +
-attitudes about the public service announcement +
-videos and about marijuana (Walther, +
-DeAndrea, Kim, & Anthony, 2010). The propagation +
-of visually and authorially anonymous +
-reviews or talk-back sites on the Web merits further +
-analysis from a SIDE perspective. +
-Signaling Theory +
-Donath (1999) was the first to suggest a theoretical +
-basis underlying the skepticism CMC +
-users often hold about the legitimacy of others’ +
-online self-presentation and how CMC facilitates +
-such deception. Prior to Donath’s position, +
-references abounded (and are still heard) regarding +
-the anonymity of the Internet facilitating +
-deception, although anonymity is a complex +
-concept with various potential meanings pertaining +
-to online interaction (see Rains & Scott, +
-2007). Anonymity’s lack of utility in the case of +
-deception is captured in the fact that individuals +
-may lie about themselves (online or off) using +
-their real names or pseudonyms. A better explanation +
-for why people mistrust others’ self-presentations +
-is needed, and Donath’s (1999) +
-approach provides a reasonable one to explain +
-why people trust many forms of information +
-that are communicated off-line but tend to mistrust +
-the kind of information individuals provide +
-about themselves that is most prevalent in +
-CMC discussions. +
-According to Donath, the fields of economics +
-and biology have contributed to the development +
-of signaling theory, which Donath then applied to +
-the evaluation of self-presentational claims in +
-text-based discussion fora. Signaling theory, +
-Donath reviews (2007), shows “why certain signals +
-are reliable and others are not. For a signal to +
-be reliable, the costs of deceptively producing +
-the signal must outweigh the benefits.” Within +
-signaling theory there are two types of signals. +
-Assessment signals are artifacts that have an inherent +
-and natural relationship with some characteristic +
-with which they are associated. An animal +
-that has very large horns, for example, must be +
-strong; strength is required to support large, +
-heavy horns. It would be impossible to support +
-very heavy horns without being strong, that is, to +
-deceive about one’s strength using such horns; +
-one could not falsely bear heavy horns if one did  +
-454——PART IV: Processes and Functions +
-not actually possess the strength to do so. +
-Conventional signals, on the other hand, bear +
-socially determined symbolic relationships with +
-their referents. Verbal claims about the possession +
-of some attribute such as strength may be conventionally +
-understood in terms of the intention of +
-the claim, but ultimately, conventional signals +
-are not as trustworthy as assessment signals. +
-Conventional signals cost little to manufacture or +
-construct, and they are therefore less trustworthy. +
-Text-based online discussions, Donath (1999) +
-proposed, are dominated by conventional signals +
-since such discussions are composed only of verbal +
-statements. Because self-descriptive claims +
-can easily be faked through verbal discourse, she +
-argues, there is (rightfully) considerable wariness +
-about whether online discussants can be trusted +
-entirely to be who they say they are. +
-Rare in the animal world, conventional +
-signals are very common in human communication. +
-The self-descriptions in online +
-profiles are mostly conventional signals—it +
-is just as easy to type 24 or 62 as it is to +
-enter one’s actual age, or to put M rather +
-than F as one’s gender. (Donath, 2007) +
-In the context of text-based CMC, Donath’s +
-(1999, 2007) application of signaling theory +
-appears to have limited predictive utility and to +
-raise certain validity questions. The perspective +
-suggests no limiting factor to the general proposition +
-that users should be suspicious of verbal +
-claims and self-descriptions in CMC. Although +
-the framework helps us understand online skepticism, +
-it does not provide much in terms of +
-variations in observers’ assessments of others’ +
-online veracity, although questions of credibility +
-in CMC have received ample attention from several +
-other perspectives (e.g., Metzger, Flanagin, +
-Eyal, Lemus, & McCann, 2003; Sundar, 2008). +
-Second, the perspective does not consider whether +
-there are indeed characteristics that are +
-transmitted sufficiently reliably through text and +
-language alone. It is hard to imagine, for instance, +
-that an individual could convey being articulate +
-or being humorous online unless the individual +
-actually possessed those characteristics. In such +
-cases, verbal behavior should constitute assessment +
-signals rather than conventional signals. +
-These and other qualities that language might +
-reliably convey are not considered in the application +
-of signaling theory to CMC. +
-To her credit, Donath (2007) has expanded the +
-application of signaling to explain the benefits +
-and potentials of social network sites in helping +
-observers assess the veracity of others’ online +
-claims. Like Walther and Parks’ (2002) warranting +
-theory (described below), she contends that the +
-ability to contact other individuals in a target’s +
-social network reduces the likelihood that the +
-target will engage in deception. From a signaling +
-theory perspective, an observer’s ability to discern +
-a target’s deception may result in social sanctions +
-or punishment for the target. These negative +
-repercussions are seen as costly in the parlance of +
-economic theory, and knowing that these costs +
-could accrue provides a disincentive for social +
-network site users to prevaricate in their profiles. +
-Thus, social network sites, unlike text-based discussion +
-systems that are divorced from an individual’s +
-off-line social network, should reduce +
-deception and increase the trust that CMC users +
-place in others. These suggestions are yet to be +
-tested, although the findings reported by Toma, +
-Hancock, and Ellison (2008) and Warkentin, +
-Woodworth, Hancock, and Cormier (2010) are +
-consistent with this notion. DeAndrea and +
-Walther (in press) found, however, that individuals +
-are quite well aware of their friends’ distorted +
-self-presentations on Facebook profiles. +
-Experiential and Perceptual +
-Theories of CMC +
-Electronic Propinquity Theory +
-The theory of electronic propinquity (Korzenny, +
-1978) received brief mention in the previous +
-edition of the Handbook’s chapter on CMC +
-(Walther & Parks, 2002). Those comments noted  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——455 +
-that relatively little attention had been paid to the +
-theory since its first appearance in 1978 and its +
-original follow-up in 1981 (Korzenny & Bauer, +
-1981; cf. Monge, 1980). Possibly because the +
-most advanced technology mentioned in its +
-introduction was interactive closed-circuit television, +
-the theory has almost escaped the attention +
-of the CMC research literature. Its formal structure +
-and the nature of its constructs, however, +
-leave it quite amenable to forms of CMC that can +
-be characterized in terms of their bandwidth and +
-interactivity. The theory has received a modicum +
-of renewed attention since 2002, including +
-empirical research that may contribute to a +
-renewal of interest in its potential. +
-The central construct in electronic propinquity +
-theory is the psychological closeness experienced +
-by communicators. Whereas physical +
-closeness or proximity is generally associated +
-with interpersonal involvement in face-to-face +
-communication, Korzenny (1978) argued that +
-communicators connected through electronic +
-media could also experience a sense of closeness, +
-or electronic propinquity. +
-The theory specified the main and interaction +
-effects on electronic propinquity from a number +
-of specific factors. The first factor is bandwidth, +
-or the capacity of a channel to convey multiplecue +
-systems (like the first factor in media richness, +
-described above, which followed propinquity +
-theory historically); the greater the bandwidth, +
-the more the propinquity. Mutual directionality +
-(like immediacy of feedback) increases propinquity, +
-as do users’ greater communication skills, +
-the lower (rather than higher) level of complexity +
-of a task, fewer communication rules, and fewer +
-choices among alternative media. These factors +
-also interact with each other, as specified in a +
-series of derived theorems: The greater the bandwidth, +
-the less the effect of task difficulty; the +
-greater users’ skills, the less the effect of more +
-communication rules; and the fewer the choices +
-among media, the less the effect of bandwidth. +
-Although the theory predated the Internet, +
-these theoretical properties provide a sufficiently +
-open-ended definitional framework in which +
-specific media may be considered even though +
-they did not exist when the theory was created. +
-Therefore CMC, with or without auditory and/or +
-visual cues, can fit neatly into electronic propinquity’s +
-calculus. Owing in part to a failed test using +
-traditional media in an experiment by Korzenny +
-and Bauer (1981), until recently, no such application +
-to CMC had been examined empirically. +
-A recent replication of electronic propinquity +
-theory’s original test has indicated greater validity +
-for the theory and has successfully applied it to +
-CMC. Walther and Bazarova (2008) identified a +
-confound in Korzenny and Bauer’s (1981) original +
-experiment that they attempted to isolate in a +
-new empirical study. The confound had to do +
-with the theory’s proposition that the fewer the +
-number of media choices one has, the greater the +
-propinquity one experiences with the remaining +
-medium, a dynamic that may have been present +
-in Korzenny and Bauer’s study but was unplanned +
-and unchecked. Walther and Bazarova investigated +
-this factor directly. They created experimental +
-groups that alternatively had two media +
-among their members (e.g., audioconferencing +
-among all members but additional videoconferencing +
-among a subset of members) or had +
-only one medium connecting everyone. Media +
-included face-to-face discussion, videoconferencing, +
-audio conferencing, and text-based chat. +
-Results supported the proposition about the +
-effect of media choice and bandwidth. Those +
-who had no choices (i.e., only one medium) +
-experienced greater propinquity using that +
-medium than did those who used the same +
-medium among two media present, when it was +
-the lower bandwidth medium of the two. For +
-example, text-based chat produced greater propinquity +
-and satisfaction ratings when chat was +
-the only channel a group was able to use, compared +
-with ratings of chat in groups where a +
-member used both chat and audio conferencing. +
-These patterns persisted along all the media +
-combinations evaluated in the study: “There +
-were no differences between ratings obtained as a +
-result of chat, voice, video, or FtF communication +
-among groups who used only one medium”  +
-456——PART IV: Processes and Functions +
-(Walther & Bazarova, 2008, p. 640), although the +
-use of two media consistently led to less propinquity +
-for the lower bandwidth medium. The +
-experiment offered further support for the theory. +
-It demonstrated complex interactions among +
-choice, bandwidth, communicator skill, and task +
-difficulty, which generally supported electronic +
-propinquity’s predictions. +
-In addition to the renewed potential for the +
-application of propinquity theory to emerging +
-media, Walther and Bazarova (2008) suggested that +
-these results may help account for discrepancies in +
-the existing literature on the social effects of CMC. +
-Numerous studies that have examined natural +
-CMC uses in field settings often indicate that it is +
-less preferred by users for relationships and group +
-maintenance than other, higher bandwidth media +
-and face-to-face interactions. In contrast, numerous +
-experimental studies show relatively high levels +
-of satisfaction and positive relational communication +
-using CMC alone under various circumstances. +
-Electronic propinquity theory’s unique +
-focus on the effects of media choice helps resolve +
-this discrepancy. It alerts us to the notion that when +
-communicators are aware or have a history of alternative +
-media options for a specific relationship, +
-CMC should be expected to be the least satisfying. +
-Where communicators are constrained to one +
-channel alone, as experiments often require, electronic +
-propinquity theory explains how users quite +
-readily apply communication skills to make the +
-remaining available medium effective and satisfying. +
-Whether there are many real-world settings +
-where users are constrained in this way to a single +
-medium is a different question, but electronic propinquity +
-theory helps unlock what had been an +
-unexplained paradox in the research literature with +
-regard to these conflicting empirical findings. +
-Social Influence Theory +
-The social influence approach to media richness +
-(Fulk, Schmitz, & Steinfield, 1990; Fulk, Steinfield, +
-Schmitz, & Power, 1987), like channel expansion +
-theory (described below; Carlson & Zmud, +
-1999), focuses on the factors that change users’ +
-perceptions about the capacities of CMC and +
-their consequent uses of the medium. It may be +
-important to note that this approach shifts the +
-definition of media richness to a perceptually +
-based phenomenon describing how expressively a +
-medium may be used. This departs from media +
-richness theory’s approach, which defines media +
-richness based on the a priori properties of media. +
-Social influence theory rejects those aspects of +
-media richness (and social presence) theory that +
-argue that certain properties of media exclusively +
-determine their expressive capabilities and their +
-utility in interpersonal (and other) domains. +
-Instead, Fulk et al. (1987) argue, the nature of +
-media and their potentials are socially constructed, +
-and the richness and utility of a medium are +
-affected by interaction with other individuals in +
-one’s social network. Following from this networkanalytic +
-perspective, the theory predicts that one’s +
-strong ties have more influence on one’s perception +
-of CMC richness than do one’s weak ties. In organizational +
-settings, these distinctions include one’s +
-close coworkers versus workers in other organizational +
-units. The authors of the model suggest that +
-social interaction with network ties may include +
-overt discussions about communication media and +
-their uses. It may also include communications +
-with one’s ties via a given CMC medium, and the +
-qualities of those exchanges also shape perceptions +
-about that medium’s potential and normative uses. +
-Social influence has received robust support in +
-previous empirical studies. Research testing the +
-model shows stronger correspondence between +
-individuals’ perceptions of e-mail’s richness and +
-those of their strongly tied coworkers than those of +
-weakly tied coworkers. Research has established the +
-cognitive and perceptual basis of these effects: +
-One’s attitudes about e-mail’s utility correspond +
-primarily with one’s perceptions about one’s +
-coworkers’ perceptions and secondarily with +
-those coworkers’ actual attitudes. These differences +
-between direct perceptions and metaperceptions +
-help demonstrate that the social influence +
-process is not a magic bullet but a communication +
-process that leads to individuals’ reconstructions of +
-others’ messages (Fulk, Schmitz, & Ryu, 1995). +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——457 +
-The social influence model has not received +
-very much research attention recently. Its developers +
-have shifted their focus after having set a +
-precedent for complex research strategies exploring +
-social influence that would not be simple to +
-replicate. Nevertheless, how users construct perceptions +
-about the potential and preferred uses +
-of newer communication technologies may be a +
-topic of renewed attention. Social network websites, +
-for example, make most visible one’s strong +
-and weak ties. They make evident what the normative +
-expressive and usage practices of one’s +
-friends are. These phenomena correspond quite +
-clearly to the theoretical factors implicated in +
-social influence theory, and future research on +
-how different groups of users evolve different +
-standards and norms for messaging via these +
-systems can benefit from a social influence +
-approach. +
-Channel Expansion Theory +
-Channel expansion theory (Carlson & Zmud, +
-1994, 1999) also takes issue with the fixed properties +
-ascribed to various media in media richness +
-theory. Whereas social influence theory +
-focuses on how dynamic interaction in a social +
-network of communicators predicts and explains +
-how users come to perceive CMC’s richness, the +
-primary focus of channel expansion theory is on +
-internal, experiential factors. The theory’s original, +
-central argument is that as individuals gain +
-more experience with a particular communication +
-medium, the medium becomes richer for +
-them (Carlson & Zmud, 1994). That is, theoretically, +
-it becomes more capable for the conduct of +
-equivocal and interpersonally oriented communication +
-tasks. With experience, the authors +
-argued, users learn how to encode and decode +
-affective messages using a particular channel. +
-The channel expansion theory was expanded +
-to include increasing familiarity with an interaction +
-partner as a second major factor affecting +
-the richness or expressiveness of a medium that +
-is used to communicate with that partner, with +
-experience related to the conversational topic +
-and organizational experience as additional, +
-potential factors (Carlson & Zmud, 1999). Social +
-influence by other communicators was posited to +
-affect richness perceptions as well. The model +
-was tested by its developers in a cross-sectional +
-survey and in a longitudinal panel study, in both +
-cases focusing only on e-mail. The first study +
-produced a moderate correlation between experience +
-using e-mail and e-mail richness perceptions +
-(see also Foulger, 1990) as well as a +
-correlation between familiarity with the conversational +
-partner and e-mail richness (Carlson & +
-Zmud, 1999). The panel study likewise found an +
-increase in perceived e-mail richness commensurate +
-with e-mail experience over time. Social +
-influence was not significant. +
-The theory lay dormant until D’Urso and +
-Rains (2008) replicated and expanded investigation +
-of the model. These researchers included +
-traditional media (face-to-face and telephone) +
-as well as text-based chat, along with e-mail, in a +
-survey of organizational users. Results were +
-fairly consistent with Carlson and Zmud’s (1999) +
-findings with respect to new media. For chat and +
-e-mail, experience with the media, and no other +
-variables, affected media richness ratings. For +
-traditional media, only social influence and +
-experience with one’s conversation partner, and +
-not experience with the medium, affected richness +
-perceptions. +
-Channel expansion theory offers an antidote +
-to the inconsistencies of media richness research +
-in a sense. The learning-based explanation that +
-channel expansion theory offers is reasonable +
-and intuitive. At the same time, other approaches +
-deal with several of the theory’s elements in more +
-sophisticated (as well as in more complicated) +
-ways. For instance, CMC users’ ability to encode +
-and decode personal and social cues is central to +
-the social information processing theory of CMC +
-(see below); the influence of others’ richness perceptions +
-is demonstrated more particularly in +
-social influence theory; and electronic propinquity +
-theory offers a different account for why +
-the same medium may offer more psychological +
-closeness and satisfaction in some circumstances  +
-458——PART IV: Processes and Functions +
-and less in others by specifying a constellation of +
-situational, media, and user characteristics. +
-Theories of Interpersonal +
-Adaptation and Exploitation +
-of Media +
-Social Information Processing +
-The social information processing (SIP) theory +
-of CMC (Walther, 1992) has become a widely +
-used framework for explaining and predicting +
-differences between text-based CMC and off-line +
-communication, and recent work has made +
-efforts to expand its scope to include newer, multimedia +
-forms of online communication. The +
-theory seeks to explain how, with time, CMC +
-users are able to accrue impressions of and relations +
-with others online, and these relations +
-achieve the level of development that is expected +
-through off-line communication. +
-The theory articulates several assumptions +
-and propositions concerning what propels these +
-effects. It explicitly recognizes that CMC is devoid +
-of the nonverbal communication cues that +
-accompany face-to-face communication. It differs, +
-however, from theories of CMC that argue +
-that the lack of nonverbal cues impedes impressions +
-and relations or reorients users’ attention to +
-impersonal states or to group-based forms of +
-relating. The SIP theory articulates the assumption +
-that communicators are motivated to +
-develop interpersonal impressions and affinity +
-regardless of medium. It further proposes that +
-when nonverbal cues are unavailable, communicators +
-adapt their interpersonal (as well as instrumental) +
-communication to whatever cues remain +
-available through the channel that they are using. +
-Thus, in text-based CMC, the theory expects +
-individuals to adapt the encoding and decoding +
-of social information (i.e., socioemotional or +
-relational messages) into language and the timing +
-of messages. Although many readers of the +
-theory have interpreted this argument to refer to +
-emoticons (typed-out smiles, frowns, and other +
-faces; e.g., Derks, Bos, & von Grumbkow, 2007), +
-the theory implicates language content and style +
-characteristics as more primary conduits of +
-interpersonal information. +
-A second major contention of SIP is that CMC +
-operates at a rate different from face-to-face communication +
-in terms of users’ ability to achieve +
-levels of impression and relational definition +
-equivalent to face-to-face interaction. Because +
-verbal communication with no nonverbal cues +
-conveys a fraction of the information of multimodal +
-communication, communication functions +
-should require a longer time to take place. +
-CMC users need time to compensate for the +
-slower rate in order to accumulate sufficient information +
-with which to construct cognitive models +
-of partners and to emit and receive messages with +
-which to negotiate relational status and definition. +
-With respect to the first major theoretical +
-contention, recent research has demonstrated +
-that communicators adapt social meanings into +
-CMC language that they would otherwise express +
-nonverbally. Walther, Loh, and Granka (2005) +
-had dyads discuss a controversial issue: face-toface +
-or via real-time computer chat. In each dyad, +
-prior to their dyadic discussion, the researchers +
-privately prompted one of the members to +
-increase or decrease his or her friendliness toward +
-the other individual by whatever means that person +
-chose to do so. The naive partner rated the ad +
-hoc confederate after the interaction was over, +
-providing ratings of the confederate’s immediacy +
-and affection dimensions of relational communication. +
-Coders then analyzed recordings of the +
-face-to-face confederates for the kinesic, vocalic, +
-and verbal behaviors that corresponded to variations +
-in immediacy and affection ratings. A number +
-of vocalic cues provided the greatest influence +
-on relational communication, followed by a +
-group of specific kinesic behaviors; the confederates’ +
-verbal behaviors had no significant influence +
-on perceptions of their immediacy and +
-affection. In contrast, in the CMC transcripts, +
-several specific verbal behaviors bore significant +
-association with differences in relational communication. +
-No less variance was accounted for  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——459 +
-by the verbal cues in CMC than the nonverbal +
-cues accounted for in face-to-face interaction. +
-This research provides confirmation about the +
-hypothetical process mechanisms of the SIP theory, +
-beyond confirmation of a relationship +
-between distal antecedents and consequents. +
-The theory is somewhat equivocal about the +
-second major element, the temporal dimension. +
-The primary theoretical explanation for the +
-additional time CMC requires for impression +
-development and relational management is that +
-electronic streams of verbal communication +
-without nonverbal accompaniments contain less +
-information than multimodal face-to-face +
-exchanges. Even in so-called real-time CMC, chat +
-communication cues are not fully duplexed in +
-terms of seeing a partner’s reactions at the same +
-time that they generate an utterance. From this +
-perspective, even a constant and uninterrupted +
-exchange of real-time CMC should provide a +
-relatively smaller accumulation of interpersonal +
-information than would face-to-face communication +
-over the same time interval. However, +
-discussions of the theory also reflect that more +
-time may be needed for relational effects to +
-accrue in CMC because CMC is generally used +
-in a more sporadic manner than face-to-face +
-communication. Online communication often +
-involves asynchronous media, that is, systems +
-that allow one communicator to create a message +
-at one time and recipients to obtain it later at a +
-point in time they choose. The SIP perspective +
-can account for both approaches to temporal +
-distortion theoretically, and both approaches +
-have been used in empirical research: Recent +
-studies have added support for SIP by using +
-strictly asynchronous communication (Peter, +
-Valkenburg, & Schouten, 2005; Ramirez, Zhang, +
-McGrew, & Lin, 2007) or real-time chat episodes +
-repeated over several consecutive days (Hian, +
-Chuan, Trevor, & Detenber, 2004; Wilson, Straus, +
-& McEvily, 2006). However, greater theoretical +
-precision would enhance understanding of the +
-theory’s scope and application. +
-The SIP theory has been expanded by researchers +
-other than its original developer to incorporate +
-media other than text-based CMC, although +
-these formulations are tentative. Tanis and +
-Postmes (2003) established that the presentation +
-of partners’ photos or the exchange of preinteraction +
-biographies of CMC users works +
-equivalently well in instilling interpersonal expectations +
-in CMC settings. Previously, SIP research +
-had been more oriented to verbal exchanges, such +
-as CMC users’ biographical disclosures, attitudinal +
-statements, and style. Therefore, it is noteworthy +
-that photographic information appears to +
-function similarly as biographical text. +
-Westerman, Van Der Heide, Klein, and Walther +
-(2008) offered a more sophisticated approach to +
-the potential effects of photos and other multimedia +
-information online within SIP framework. +
-These researchers reconsidered SIP’s root proposition +
-that lesser bandwidth media transmit less +
-information per exchange than do greater bandwidth +
-media, affecting the rate of impression +
-formation and relational development. They +
-examined various forms and channels of personal +
-information from this perspective. As a result, +
-they argued that some mediated forms of information +
-are faster (i.e., they transmit more social +
-information in a respective time interval, e.g., +
-photos or videos) and others are slower. This +
-simple assertion is consistent with SIP; yet an +
-expanded view of faster and slower media allows +
-for greater scope and a wider range of predictions +
-about new, multimodal media than the theory +
-was originally conceived to explain. +
-Despite these potential adjustments with +
-which to integrate visual information in the SIP +
-framework, recent studies have demonstrated +
-considerably limited additional effects on attraction +
-and uncertainty reduction when additional +
-modalities accompany text-based CMC. In one +
-study, Antheunis, Valkenburg, and Peter (2007) +
-compared face-to-face dyadic communication +
-with an instant messaging system, and a hybrid +
-instant messenger that displayed visual information +
-about a dyadic partner alongside textual CMC. +
-After a get-to-know-you session, no significant +
-differences in interpersonal attraction arose +
-between these conditions. Visual cues actually  +
-460——PART IV: Processes and Functions +
-increased the frequency of disclosures and personal +
-questions, in contrast to previous findings +
-that disclosure and personal questions were proportionately +
-more frequent in CMC than in faceto-face +
-interactions (Tidwell & Walther, 2002). +
-Finally, a recent examination of uncertainty +
-reduction processes via social network sites +
-focused explicitly on the potential obsolescence +
-of SIP theory in light of new media characteristics +
-providing information aside from the interactive +
-exchanges on which SIP traditionally +
-focuses. Another study by Antheunis, Valkenburg, +
-and Peter (2010) argued that social network sites +
-provide an abundance of asynchronous and +
-unintrusive biographical, multimodal (pictorial), +
-and sociometric information about other +
-people. Therefore, they predicted that these +
-alternative forms of social information should +
-be expected to be the primary sources of uncertainty +
-reduction about others, without need of +
-recourse to interactive communication via text. +
-Results of the study showed that despite the +
-appeal of these newer forms of information display, +
-interactive communication contributed the +
-most to uncertainty reduction about another +
-individual. +
-Hyperpersonal CMC +
-The hyperpersonal model of CMC (Walther, 1996) +
-proposes a set of concurrent theoretically based +
-processes to explain how CMC may facilitate +
-impressions and relationships online that exceed +
-the desirability and intimacy that occur in parallel +
-off-line interactions. The model follows four common +
-components of the communication process +
-to address how CMC may affect cognitive and +
-communication processes relating to message +
-construction and reception: (1) effects due to +
-receiver processes, (2) effects among message senders, +
-(3) attributes of the channel, and (4) feedback +
-effects. The model has received a great deal of +
-attention in the literature. At the same time, extensions +
-and revisions to the model have been proposed +
-on the basis of both conceptual and empirical contributions. +
-Certain aspects of the model remain +
-underresearched—such as the holistic integrity of +
-its subcomponents as well as the reciprocal effects +
-of feedback—although some progress has been +
-made with respect to these issues. +
-Receivers. When receiving messages from others +
-in CMC, an individual may tend to exaggerate +
-perceptions of the message sender. In the absence +
-of the physical and other cues that face-to-face +
-encounters provide, rather than fail to form an +
-impression, receivers fill in the blanks with regard +
-to missing information. This often takes the form +
-of idealization if the initial clues about another +
-person are favorable. The original articulation of +
-the model drew explicitly on SIDE theory (Lea & +
-Spears, 1992) in formulating receiver dynamics. +
-The SIDE model also describes how CMC users +
-make overattributions of similarity when communicating +
-under conditions of visual anonymity +
-if contextual cues suggest that a conversational +
-partner shares some salient social identity with +
-the receiver. It further proposes that communicators +
-experience heightened attraction in these +
-circumstances. The SIDE model argues that the +
-specific form of attraction is focused on one’s +
-attachment to the group identity rather than to +
-the individual person. +
-Recent rearticulations of the hyperpersonal +
-model, however, have attempted to broaden the +
-concepts related to receiver dynamics (see Walther, +
-2006). The hyperpersonal approach now suggests +
-that an initial impression may be activated not +
-only by group identifications but through individual +
-stereotypes, such as personality characteristics, +
-or due to the vague resemblance of an +
-online partner to a previously known individual +
-(see Jacobson, 1999). Analysis of online impressions +
-using social relations analysis (Kenny, 1994), +
-which assesses how uniform or differentiated +
-one’s impressions of other group members are, +
-offers a promising approach to the question of +
-group- or interpersonally based impressions in +
-CMC (see Markey & Wells, 2002). +
-Senders. Text-based CMC facilitates selective selfpresentation. +
-Online, one may transmit only cues  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——461 +
-that an individual desires others to have. It need +
-not be apparent to others what one’s physical +
-characteristics are (unless one discloses them +
-verbally), nor do individuals generally transmit +
-unconscious undesirable interaction behaviors +
-such as interruptions, mismanaged eye contact, +
-or nonverbal disfluencies of the kind that detract +
-from desired impressions face-to-face. Instead, +
-CMC senders may construct messages that portray +
-themselves in preferential ways, emphasizing +
-desirable characteristics and communicating in a +
-manner that invites preferential reactions. Selfdisclosure +
-quite naturally plays a role in this +
-process, by which individuals not only disclose +
-what content they wish to be known but also, +
-through disclosure, breed intimacy. Research has +
-found that disclosure and personal questions +
-constitute greater proportions of utterances in +
-online discussions among strangers than they do +
-in comparable face-to-face discussion (Joinson, +
-2001; Tidwell & Walther, 2002). This may be a +
-simple adaptation to the lack of nonverbal +
-expressive behavior, which would normally provide +
-uncertainty-reducing information. Yet CMC +
-users’ disclosures are more intimate than those of +
-face-to-face counterparts, suggesting a strategic +
-aspect to this difference as well. +
-Apart from explicit disclosures, much of what +
-senders selectively self-present is conveyed +
-through the content of the exchanges in terms of +
-how communicators express their evaluations of +
-various subjects, their agreement with partners, +
-word choice, and any number of ordinary expressions +
-of affinity. A recent study (Walther, Van Der +
-Heide, Tong, Carr, & Atkin, 2010) asked one +
-member of an online dyad, who was about to +
-discuss the topic of hamburgers with an online +
-partner, to behave online in a way that prompted +
-the other person to like or to dislike the individual. +
-The significant differences in liking for the +
-actor following the CMC conversation were associated +
-with the actor’s level of agreements versus +
-disagreements and concurrence versus divergence +
-in statements about the other partner’s +
-favorite hamburger. Online (and perhaps elsewhere), +
-we manipulate our desirability to others +
-not so much by overt statements of interpersonal +
-affect but through the way we complement or +
-contest others’ views of things in the world. In other +
-research, systematic differences among individuals’ +
-construction of stories about themselves +
-online led to changes in their self-perceptions. +
-Gonzales and Hancock (2008) asked participants +
-to write about their experiences in a manner that +
-would lead others to perceive them as either +
-extraverted or introverted. Half of the participants +
-in the experiment posted these responses +
-in a blog, presumably accessible to other CMC +
-users, whereas the other half of the participants +
-recorded their answers in a private document for +
-ostensible analysis at a later time, anonymously. +
-The blog writers generated significantly different +
-self-perceived extraversion/introversion scores +
-following the experience, in accordance with the +
-characteristic they had been assigned. Gonzales +
-and Hancock concluded that selective selfpresentation +
-online provides a potent influence +
-not only on others but also on the transformation +
-of an individual’s self, a phenomenon they +
-called “identity shift.” +
-Channel. The third dimension of the hyperpersonal +
-model involves characteristics of the channel +
-and how CMC as a medium contributes to +
-the deliberate construction of favorable online +
-messages. One part of the channel factor focuses +
-on the mechanics of the CMC interface, suggesting +
-that users exploit the ability to take time to +
-contemplate and construct messages mindfully. +
-In many CMC applications (especially asynchronous +
-systems), users may take some time to +
-create optimally desirable messages without +
-interfering with conversational flow, very much +
-unlike the effects of face-to-face response latencies. +
-The hyperpersonal model further suggests +
-that CMC users capitalize on the ability to edit, +
-delete, and rewrite messages to make them reflect +
-intended effects before sending them. The introduction +
-of the model further suggested that +
-CMC users may redirect cognitive resources into +
-enhancing one’s messages, without the need to +
-pay attention to the physical behaviors of one’s  +
-462——PART IV: Processes and Functions +
-conversational partner or oneself, or to the ambient +
-elements where one is physically located +
-when communicating (in contrast to these +
-demands on attention in face-to-face conversations). +
-CMC users can focus their attention on +
-message construction to a greater extent than +
-they would in face-to-face conversations. +
-Recent research supported a number of these +
-suggestions (Walther, 2007). A study led college +
-student participants to believe that they were +
-joining an asynchronous discussion with a prestigious +
-professor, who was described in much +
-detail; with a relatively undesirable high school +
-student in another state, also described in detail; +
-or with another college student, about whom no +
-details were provided except for the student’s +
-name. Participants’ message composition was +
-recorded in real time and later coded and rated, +
-and a different group of participants provided +
-ratings of how desirable each type of target +
-would be as an interaction partner. Results of the +
-study revealed that the more desirable the partner +
-was, the more editing (deletions, backspaces, +
-and insertions) the participants exercised in +
-composing their messages to that partner. The +
-degree of editing corresponded to the degree of +
-relational affection ascribed to the messages by +
-raters. Participants self-reported their level of +
-mindfulness during message production, which +
-had been expected to differ based on the attractiveness +
-of the ostensible message target. It did +
-not, and neither did the time they spent composing +
-their messages differ as a result of the different +
-types of targets. However, those who were +
-more mindful spent more of their time editing +
-the messages they had written, whereas those +
-who were lower in mindfulness spent more time +
-choosing what to write. These results add a level +
-of verification to the model’s contention that +
-CMC users exploit the unique mechanical features +
-of the medium to enhance relational qualities +
-of their messages. +
-Another facet of the channel component of +
-the hyperpersonal model has been more difficult +
-to interpret, and research results have challenged the +
-model’s original assertions about asynchronous +
-versus synchronous CMC. The model originally +
-posited that asynchronous CMC allowed users to +
-avoid the problems of entrainment associated +
-with face-to-face meetings. Entrainment, in the +
-small group communication literature (Kelly & +
-McGrath, 1985), refers to the ability to synchronize +
-attention and interaction with collaborators. +
-It is proposed to be difficult to accomplish when +
-participants have competing demands on their +
-time and attention. Time pressures work against +
-entrainment in face-to-face meetings, leading +
-communicators to neglect group maintenance +
-behaviors in favor of impersonal, task-related +
-discussions. Since CMC users working asynchronously +
-can interact with others at times that are +
-convenient and available to them, the model suggested +
-that CMC should not suffer from a lack of +
-maintenance behavior. CMC users would be +
-more likely to engage in off-task, interpersonal +
-discussions than in face-to-face meetings since, +
-without meeting in real time, there is no time +
-pressure constraining such exchanges. +
-This aspect of the model was challenged very +
-quickly. Roberts, Smith, and Pollock’s (1996) ethnographic +
-observations and interviews reflected +
-that individuals who enter real-time, multiplayer +
-online games and chat systems (as opposed to +
-asynchronous discussions) very rapidly exhibit +
-sociable exchanges. Likewise, Peña and Hancock +
-(2006) demonstrated that the conversations in +
-a real-time multiparty sword-fighting game +
-reflected more socio-emotional utterances than +
-game-related statements even during online +
-duels. The sociability benefits originally ascribed +
-to asynchronous CMC in the introduction of the +
-model are fairly clearly an aspect of many synchronous +
-systems as well, at least those in which +
-socializing is a goal that users bring to the system. +
-A recent review of communication that takes +
-place in certain online, real-time, role-playing +
-games describes a great proportion and a wide +
-variety of interpersonal communication behaviors +
-among associates and fellow “clan” members +
-(Klimmt & Hartmann, 2008). Although these +
-findings suggest greater scope for the development +
-of hyperpersonal dynamics, the entrainment  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——463 +
-explanation has not been tested since the model +
-was developed, and the conceptual and empirical +
-status of this aspect of the channel component of +
-the model is unclear. +
-Feedback. The hyperpersonal model of CMC +
-suggested that the enhancements provided by +
-idealization, selective self-presentation, and +
-channel effects reciprocally influenced matters, +
-forming a feedback system by which the CMC +
-intensified and magnified the dynamics that each +
-component of the model contributes. That is, +
-when a receiver gets a selectively self-presented +
-message and idealizes its source, that individual +
-may respond in a way that reciprocates and reinforces +
-the partially modified personae, reproducing, +
-enhancing, and potentially exaggerating +
-them. The manner in which the dynamics of +
-these reciprocated expectations may modify participants’ +
-character was suggested to reflect the +
-process of behavioral confirmation. +
-Behavioral confirmation (Snyder, Tanke, & +
-Berscheid, 1977) describes how one interaction +
-partner’s impression about a target partner leads +
-the first partner to behave and how that behavior +
-alters the responses of the target partner in +
-return. The original behavioral confirmation +
-study involved male participants who were +
-shown photos priming them to believe that their +
-upcoming female telephone interaction partners +
-were physically attractive or unattractive (even +
-though the actual partners were not really those +
-depicted in the photos but were randomly +
-selected female participants). Not only did this +
-expectation affect the males’ involvement, it +
-affected the females’ personality-related responses +
-as well, as revealed in outside raters’ evaluations +
-of the females’ personalities based on audio +
-recordings of their conversations. The hyperpersonal +
-model appropriated this construct, suggesting +
-that one’s idealized impressions of an +
-online partner may lead a CMC user to reciprocate +
-based on that impression, transmitting messages +
-that, in turn, may shape the partner’s +
-responses, shifting the target’s personality in +
-the direction of the communicators’ mutually +
-constructed and enacted impression. In this way, +
-feedback may intensify the hyperpersonal effects +
-of idealization, selective self-presentation, and +
-channel exploitation. +
-The feedback component of the hyperpersonal +
-model has received little formal research attention +
-until recently. One study (Walther, Liang, et al., +
-2011) examined whether feedback to a CMC +
-communicator enhanced the identity shift phenomenon +
-described by Gonzales and Hancock +
-(2008; see above). As Gonzales and Hancock had +
-done, this experiment called on half the participants +
-to answer several questions as if they were +
-extraverted and the other half, as if introverted. +
-Participants posted their responses to a blog or +
-pasted them into a Web-based form. Departing +
-from Gonzales and Hancock, in each condition, +
-participants either did or did not receive feedback +
-confirming their (extraverted or introverted) personality +
-performances. When participants subsequently +
-completed self-report measures of their +
-extraversion/introversion, those who received +
-feedback expressed more extreme scores in the +
-direction of the initial prompting. This study +
-also helps establish a link between two components +
-of the hyperpersonal model—selective selfpresentation +
-and feedback—showing that the +
-activation of these components jointly produces +
-stronger effects than in isolation. +
-Several CMC studies have generated findings +
-consistent with a behavioral disconfirmation +
-effect (see Ickes, Patterson, Rajecki, & Tanford, +
-1982; Burgoon & Le Poire, 1993). Behavioral +
-disconfirmation takes place when one individual +
-anticipates an unpleasant interaction with a target +
-person and, to avert the unpleasantness, overaccommodates +
-in order to improve the person’s +
-demeanor. One was the Walther (2007) study +
-described above, in which participants anticipated +
-online communication with a high school– +
-age loner, a college student, or a professor. +
-Despite pretest indications that the high schoolers +
-were the least desired communication partners, +
-male participants who believed that they +
-were communicating with a male high schooler +
-expressed greater editing and affection than with  +
-464——PART IV: Processes and Functions +
-a male peer or professor. No voice-based or faceto-face +
-comparisons were done in that study. +
-As discussed earlier, two recent studies +
-explored the effects of preinteraction expectancies +
-on subsequent impressions following CMC +
-or voice-based communication (Epley & Kruger, +
-2005; Walther, DeAndrea, & Tong, 2010). +
-Manipulations in both studies instilled preinteraction +
-expectancies among interviewers regarding +
-their partners’ high or low intelligence. +
-Manipulations in both studies involved the bogus +
-presentation of one of two sets of a partner’s +
-ostensible photograph, grade point average, +
-major, and self-reported greatest high school +
-achievement. In Epley and Kruger’s (2005) +
-research, half the interviewers used a phonelike +
-system to speak to a real interviewee, and half the +
-interviewers used CMC to obtain responses that +
-were transcribed from a person other than the +
-actual interviewee. The results superficially +
-appear to reflect greater behavioral confirmation +
-in CMC than on the phone: Interviewers’ posttest +
-assessments of interviewees’ intelligence were +
-different in CMC but not in voice conditions. +
-The methodology in that study, however, was +
-such that the CMC interviewer could not actually +
-have influenced his or her partner’s behavior. +
-Walther, DeAndrea, and Tong’s (2010) replication +
-involved actual interviewees in both voice +
-and CMC conditions. The post-CMC ratings +
-indicated relatively greater intelligence assessments +
-than did those following the voice-based +
-interviews, reflecting behavioral disconfirmation +
-in CMC relative to voice. Further research is +
-exploring the reasons for these voice versus CMC +
-differences in confirmation and disconfirmation. +
-Extensions. In addition to research that has added, +
-supported, or challenged the hyperpersonal model’s +
-claims, a variety of extensions to the model +
-have been made, and it has been applied to new +
-social technologies as well. +
-Research exploring the dynamics of online +
-date-finding systems has applied aspects of the +
-hyperpersonal model in several ways. Many of +
-these systems require users to create profiles that +
-feature photos and self-descriptions. Ellison, +
-Heino, and Gibbs’s (2006) interviews with online +
-daters revealed that users make overattributions +
-from minimal cues that prospective dates exhibit. +
-These include gross inferences based on spelling +
-errors and projections about individuals’ character +
-on the basis of what time of day or night he or she +
-initiates a date request. Gibbs, Ellison, and Heino +
-(2006) also drew on selective self-presentation +
-principles in their documentation of the dilemmas +
-faced by daters when honest self-presentations +
-produce fewer dates than do self-aggrandizing or +
-deceptive self-presentations (see also Whitty, 2008). +
-Research on deceptive self-presentation in +
-online dating profiles has made particular use of +
-the hyperpersonal model. Innovatively acquired +
-data demonstrate that most online daters misrepresent +
-their age, weight, and/or height online +
-(Toma et al., 2008; see also Hall, Park, Song, & +
-Cody, 2010). In several cases, these findings have +
-been attributed to CMC’s facility for selective +
-self-presentation and editing under asynchronous +
-communication conditions (Toma et al., +
-2008). This hyperpersonal perspective has most +
-recently been applied to the manner in which +
-dating system users select or retouch the photographs +
-they post to their electronic profiles +
-(Hancock & Toma, 2009). +
-Additional work has added new explanatory +
-extensions to the model. Jiang, Bazarova, and +
-Hancock (2011) developed a framework for +
-understanding the exceptional impact of selfdisclosure +
-on intimacy in CMC compared with +
-face-to-face communication. Although individuals +
-disclose proportionately more, and more +
-intimately, in CMC than in face-to-face communication +
-(Tidwell & Walther, 2002), questions +
-remained over whether receivers (over) interpret +
-disclosures in a way that increases intimacy in +
-CMC more intensively than in off-line interactions. +
-Jiang et al. (2011) hypothesized that the +
-degree to which receiving disclosure from a conversational +
-partner affects intimacy is shaped by +
-the attributions a receiver makes for the partner’s +
-motivation to disclose. A 2 × 2 experiment included +
-CMC chat versus face-to-face interactions between  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——465 +
-a naive participant and a confederate who offered +
-several personal disclosures in one condition and +
-no disclosures in a control condition. Posttest +
-measures revealed that the CMC participants +
-receiving disclosures experienced greater intimacy +
-than did face-to-face participants. Among +
-those who were exposed to a greater degree of +
-disclosure, the CMC participants more frequently +
-perceived that the discloser’s behavior +
-was motivated by some aspect of their relationship +
-rather than by the medium or the discloser’s +
-disposition, compared with the face-to-face participants. +
-The type of attribution fully mediated +
-the relationship between the disclosure-bymedium +
-interaction and intimacy. In addition to +
-documenting a hyperpersonal effect of disclosure +
-on intimacy, this study provided a new attributional +
-mechanism to explain the effect, which is +
-also affected by the medium. +
-A self-attribution dynamic may also be operating +
-online that leads to exaggerated intimacy as +
-a result of online self-disclosure, a hypothesis +
-that has not appeared in the literature previously. +
-Although it is commonly understood that when +
-another person discloses to us, we experience +
-intimacy with that person, Collins and Miller’s +
-(1994) meta-analysis of the relationship between +
-disclosure and liking demonstrates an alternative +
-connection as well: When we disclose to another +
-person, our own disclosure increases our feelings +
-of intimacy toward the recipient. Thus, when +
-users naturally adapt to the absence of nonverbal +
-cues in CMC by disclosing proportionately more +
-than they do in face-to-face interaction (Joinson, +
-2001; Tidwell & Walther, 2002), it may be due to +
-their own expression of relatively greater disclosure +
-(in addition to or instead of the reception of +
-others’ disclosures) that they attribute greater +
-intimacy to disclosive CMC conversations. +
-Although this contention warrants empirical +
-verification, it suggests an interesting contribution +
-to the hyperpersonal cycle. +
-Another form of self-perception affecting +
-intimacy can be hypothesized on the basis of +
-findings that it takes several times longer to have +
-a conversation online than exchanging the same +
-amount of verbal content in a face-to-face meeting +
-(see Tidwell & Walther, 2002). If CMC chatters +
-have an online conversation that feels as +
-though it should only have taken an hour but +
-turns out to have taken four hours, and if the +
-communication rate differential is not apparent +
-to CMC interactants (as it is apparently unapparent +
-to online game players; Rau, Peng, & Yang, +
-2006), this temporal distortion may also lead to +
-exaggerated inferences about the desirability of +
-the online partner. When time seems to pass +
-more quickly than it actually does, people attribute +
-enjoyment to the events that occurred during +
-that time (Sackett, Nelson, Meyvis, Converse, +
-& Sackett, 2009). +
-Other researchers have also examined the role +
-of disclosures in the development of relatively +
-more intimate relations online and their effects. +
-Valkenburg and Peter (2009) identify three relationships +
-among four specific processes that +
-explain how CMC may be related to improvements +
-in adolescents’ well-being. For reasons that +
-have appeared in the literature (see above; for a +
-review Kim & Dindia, 2011; see also Schouten, +
-Valkenburg, & Peter, 2007), the first important +
-relationship in the model is the effect of CMC in +
-promoting online self-disclosure. Drawing on +
-extensive literature, Valkenburg and Peter (2009) +
-proceed to connect self-disclosure with the development +
-of higher quality relationships among +
-people. Finally, the authors point out the connection +
-between high-quality relationships and +
-development of psychological well-being. The +
-first two linkages in particular implicate CMC as +
-a catalyst in the relationally-based development +
-of adolescent adjustment. +
-In contrast to Valkenburg and Peter’s depiction +
-of the beneficial effects of CMC to wellbeing, +
-another application of the hyperpersonal +
-model is seen in Caplan’s (2003) approach to the +
-study of problematic Internet use. Caplan focuses +
-on the usage and consequences of CMC by individuals +
-who have social skill deficits in their +
-face-to-face communication abilities and who +
-experience disruptive communication-related +
-anxieties. To such people, Caplan has shown that  +
-466——PART IV: Processes and Functions +
-Internet interaction is especially appealing, particularly +
-real-time discussion systems. Because +
-CMC provides individuals greater control over +
-their messages and their self-presentation, it +
-reduces anxiety (see also Amichai-Hamburger, +
-2007). Under these conditions, individuals may +
-develop what Caplan (2005) refers to as a preference +
-for online social interaction, “characterized +
-by beliefs that one is safer, more efficacious, +
-more confident, and more comfortable with +
-online interpersonal interactions and relationships +
-than with traditional (face-to-face) social +
-activities” (p. 723). This use of CMC is paradoxical +
-and problematic, according to Caplan’s +
-research, because such individuals experience a +
-decline in their off-line social skills in conjunction +
-with their more socially rewarding online +
-interactions. +
-Warranting +
-A new theoretical construct, known as the warranting +
-construct, was introduced in the previous +
-edition of the Handbook of Interpersonal Communication +
-(Walther & Parks, 2002). Warranting +
-pertains to the perceived legitimacy and validity +
-of information about another person that one +
-may receive or observe online. Individuals often +
-come to learn quite a lot about each other +
-through discussions in topical online discussion +
-groups or through online role-playing games +
-(see Parks & Floyd, 1996; Parks & Roberts, 1998), +
-as well as from personal homepages and other +
-forms of online interaction and self-presentation, +
-including online dating sites (see Ellison et al., +
-2006). However, as Donath (1999) explained, it is +
-widely suspected that the information one +
-obtains through interaction in such venues leaves +
-open the possibility for distorted self-presentations +
-and outright deception with respect to participants’ +
-off-line characteristics. As a relationship +
-develops online, there may come a point at which +
-it becomes very important to interactants to have +
-information that they believe reliably describes a +
-partner’s off-line characteristics. This may become +
-especially acute if they decide to initiate an offline +
-meeting, as many online friends and prospective +
-romantic partners decide to do (Parks & +
-Roberts, 1998). +
-The introduction of the warranting construct +
-argued that an individual is less likely to distort +
-his or her self-presentation when the receiver has +
-access to other members of the sender’s social +
-circle, since others can corroborate the individual’s +
-real-life characteristics and hold that person +
-accountable for misrepresentation. To increase a +
-partner’s confidence in one’s self-descriptions, an +
-individual may make efforts to put an online +
-partner in touch with members of the individual’s +
-off-line network. +
-The greater value of the warranting construct is +
-found in its definition of what kind of information +
-provides more confidence to receivers about the +
-potentially true nature of an individual’s off-line +
-self. From this perspective, receivers are expected to +
-be more confident about their impressions based +
-on information that is more likely to warrant, or +
-connect, the online persona to the off-line body +
-and person (see Stone, 1995). Information is more +
-likely to be seen as truthful to a receiver to the +
-extent that the receiver perceives it to be “immune +
-to manipulation by the person to whom it refers,” +
-according to Walther and Parks (2002, p. 552). +
-They argued that CMC users may take deliberate +
-steps to provide online partners with information +
-having relatively great warranting value by using +
-links to individuals in one’s social network or +
-hyperlinks to websites or archives containing information +
-about the user over which the user himself +
-or herself has no control. +
-Recent research has provided several empirical +
-tests of the warranting construct. Although +
-warranting was originally conceptualized in the +
-context of relationships originating in text-based +
-online discussions, recent research has applied +
-and extended the construct to contemporary +
-multimedia websites in interesting ways. The first +
-reference to warranting came in a study of +
-impression management in online dating sites. +
-Ellison et al. (2006) reported that online date  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——467 +
-seekers warrant their claims about their proclivities +
-or participation in certain activities by +
-including photographs on their user profiles that +
-depict them engaged in the activity they are +
-claiming. Showing oneself rock climbing, for +
-instance, would be difficult to manipulate or +
-manufacture if it was not an individual’s actual +
-activity (see Donath, 1999, and below). Other +
-research from an online dating context (Toma +
-et al., 2008) found that individuals who used +
-online date-finding services distorted their online +
-self-presentation to a lesser extent the more their +
-off-line acquaintances knew they were using +
-these services. Similarly, Warkentin et al. (2010) +
-investigated whether individuals’ displays of +
-information that could be used to hold them to +
-account for self-presentations affected the frequency +
-and degree of deception they displayed +
-with respect to their claims about demographic +
-characteristics and personal tastes and preferences. +
-Although chat systems featured more +
-deception than was present in social network +
-profiles and e-mail, the presence of cues to offline +
-identity in any of these platforms reduced +
-the level of deception in that medium, according +
-to Warkentin et al. +
-Walther, Van Der Heide, Hamel, and Shulman +
-(2009) tested warranting experimentally by juxtaposing +
-flattering versus unflattering statements +
-about an individual on mock-up Facebook profiles. +
-The comments were made to appear to have +
-been posted by the profile owner or by the owner’s +
-Facebook friends. Facebook provides a format +
-in which an individual can indicate qualities +
-about himself or herself via “about me” descriptions, +
-favorite quotations, current activities, and +
-so on and where one’s acquaintances can also +
-post comments reflecting the activities and characteristics +
-of the profile host via postings on the +
-host’s “wall” (and other commenting systems). +
-When individuals’ suggestions about their own +
-physical attractiveness (either positive and selfpromoting +
-or negative and self-denigrating) +
-were contradicted by the cues contained in wall +
-postings from friends, observers’ ratings of the +
-profile owner significantly reflected the friends’ +
-comments more than the profile owner’s selfclaims. +
-A replication focusing on profile owners +
-and friends’ assessments of an individual’s extraversion +
-provided more ambiguous results. In +
-related research, an experiment that varied only +
-the coefficients representing the number of +
-friends a Facebook profile owner appeared to +
-have found a curvilinear relationship between +
-the number of one’s friends and the observers’ +
-ratings of the profile owner’s popularity and +
-social attractiveness (Tong, Van Der Heide, +
-Langwell, & Walther, 2008). Although the sociometric +
-friend coefficient did not contradict any +
-particular self-generated claim of the profile +
-owner, its effect nevertheless reinforces the influential +
-nature of online information about a user +
-that is beyond the immediate reach of the user to +
-manipulate. A similar study by Utz (2010) examined +
-observers’ ratings of a profile owner’s popularity +
-and social attractiveness via the Dutch +
-Hyves social network site. Profile mock-ups +
-reflected variations in self-claims for extraversion, +
-the photographically depicted extraversion +
-of nine of one’s friends, and the number of +
-friends a profile owner had. An interaction effect +
-between the number of friends and the apparent +
-extraversion of friends significantly affected the +
-social attractiveness ratings of the profile owner. +
-The warranting principle remains a relatively +
-new construct at this time, although its empirical +
-application in contemporary multimedia systems +
-suggests that it is likely to see additional +
-rather than decreased use. Concerns about the +
-legitimacy of others’ online self-presentations +
-has been a pernicious issue related to CMC since +
-before the widespread diffusion of the Internet +
-(see Van Gelder, 1985), and sensationalistic +
-accounts of identity deception and manipulation +
-still attract headlines (Labi, 2007). Likewise, as +
-systems for meeting new friends and lovers shift +
-from the casual discussion site to purposive +
-online dating sites, concerns about others’ online +
-authenticity continues (Lawson & Leck, 2006). +
-Theoretical structures that help explain how  +
-468——PART IV: Processes and Functions +
-CMC users assess the veridicality of others’ +
-online self-presentations may increase in value. +
-Efficiency Framework +
-A new framework was developed to resolve previously +
-contradictory findings about satisfaction +
-with, and the effectiveness of, CMC collaboration. +
-Its investigation has incorporated very novel +
-CMC technologies and has implicated presence +
-as a mediating factor. +
-The framework’s developers, Nowak, Watt, and +
-Walther (2005, 2009), noted that many studies of +
-CMC generated relatively low ratings on interpersonal +
-satisfaction and related notions (typically in +
-field experiments or surveys) compared with ratings +
-of face-to-face communication or video communication. +
-Although researchers are frequently +
-aware of the known linkage between interpersonal +
-cohesiveness and productivity or quality, many of +
-the same studies in which CMC earned lower +
-sociability ratings found no deleterious effects of +
-CMC on task accomplishment. For example, +
-Galagher and Kraut (1994) found that text-based +
-CMC groups were less satisfied with their communication +
-than video-mediated groups but that +
-there were no significant differences in the quality +
-of the outputs that these conditions produced. +
-Research assessing CMC often relies on measurements +
-of its subjective appeal and does not consider +
-its instrumental utility for communicative +
-tasks independently. +
-Nowak et al. (2009) argue that users are likely +
-to conflate their impressions of CMC’s presence +
-and satisfaction with their estimates of its utility. +
-Enjoyment or frustration responses override an +
-individual’s objective assessment of effectiveness, +
-and individuals may be expected to dislike CMC +
-when there are easier alternatives (see Korzenny’s, +
-1978, electronic propinquity theory, described +
-above). People are cognitive and behavioral +
-misers, as Nowak et al. (2009) note, and prefer to +
-do a task using less effort than using more effort. +
-Compared with face-to-face communication, +
-CMC is more effortful. Face-to-face communication +
-is intuitive and provides rapid exchange of +
-information through multiple modalities. Drawing +
-on SIP theory, CMC may be just as capable as +
-face-to-face interaction in achieving task and +
-social outcomes, but it requires more time and +
-effort, which are inherently less desirable in most +
-cases than doing things in an easier way. There is +
-a natural efficiency to face-to-face communication +
-that is often satisfying. +
-Satisfaction and utility may be unrelated, +
-however, or even inversely related, depending on +
-the task. When people collaborate on writing +
-something together, for instance, talk is only +
-useful to a point. In contrast, if collaborators +
-plan, organize, and execute a writing task via the +
-written (and stored and editable) medium of +
-CMC, it may provide a greater efficiency in the +
-long run, since things have been made recorded, +
-retrievable, and reusable in a way that speech is +
-not. This process is not less effortful than talk. +
-Greater effort, however, in addition to being +
-frustrating, may lead to better outcomes. In this +
-way, the efficiency framework attempts to +
-explain how, within and across studies, CMC +
-may be rated as socially unsatisfactory but, nevertheless, +
-may offer instrumental benefits. To +
-evaluate CMC on an affective basis alone, which +
-is common, may be misleading from a utilitarian +
-perspective. +
-Empirical research on the efficiency framework +
-has been extremely limited. One study involved +
-small groups collaborating on the preparation of +
-presentations for five weeks, using face-to-face +
-meetings, text-based real-time chats at specific +
-times, asynchronous text-based conferencing, +
-real-time videoconferencing, or an asynchronous +
-video communication system that allowed members +
-to record, leave, and play multimodal messages +
-to and from one another (Nowak et al., +
-2009). Consistent with previous research and +
-the efficiency framework’s predictions, selfadministered +
-questionnaires showed higher scores +
-on presence and conversational involvement for +
-face-to-face communication above all other conditions. +
-A greater number of cue systems also +
-led to greater subjective project quality and satisfaction, +
-as did synchronous (compared with  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——469 +
-asynchronous) media. With respect to the objective +
-quality of their projects, however, external +
-coders’ ratings identified the asynchronous video +
-condition as having facilitated the best actual +
-work, with no other differences between conditions. +
-Real-time versus asynchronous comparisons +
-did not affect the quality of the work. +
-Although this perspective seems especially +
-suited for the study of mediated collaborations, +
-its central lessons may apply to a variety of +
-interpersonal as well as instrumental settings as +
-media characteristics evolve: Those media that +
-are the easiest to use may not, in fact, offer +
-the greatest instrumental benefit. As interface +
-options increase and become more natural, +
-more research will be needed that separates +
-affective reactions from those pertaining to +
-interaction goals. In strictly recreational social +
-settings, these two aspects—social and purposive +
-outcomes—may be isomorphic. As new +
-electronic media such as avatar-based systems +
-and desktop video are employed for an increasing +
-number of activities, including the common +
-instrumentalities that make up so much of the +
-maintenance of ongoing relationships, whether +
-easier is better or not, will deserve continued +
-reexamination. +
-ICT Succession +
-Perhaps the most recent new framework about +
-CMC is Stephens’s (2007) prescriptive formulation +
-involving the strategic sequencing of messages +
-across multiple communication channels. +
-This approach recognizes different forms of +
-information and communication technologies +
-(ICTs), including traditional media, face-to-face +
-channels, and newer forms of CMC. It primarily +
-concerns how combinations of ICTs predict +
-communication effectiveness in organizational +
-communication, although it includes predictions +
-related to the use of the media for “tasks that are +
-personal and social in nature” (p. 499). +
-In terms of its structure, the ICT succession +
-model presents several propositions inferred by +
-the author from principles and findings in a wide +
-variety of literatures, rather than deriving them +
-from a set of related higher order constructs. The +
-major theoretical terms of the model can be +
-identified as (a) successive (vs. single) message +
-transmissions and (b) complementary (vs. singular) +
-channel usage. The central proposition of the +
-model is that the repetition of a message through +
-two different types of communication channels +
-causes the greatest communication effectiveness +
-and efficiency (for certain types of tasks). For +
-example, a message sent once face-to-face might +
-be followed up by e-mail, or vice versa, which +
-should be more effective than repeating messages +
-using a single medium (or no repetitions at all). +
-Among these terms and relationships, singular +
-versus successive messaging is easily defined: +
-A communicator may send a message once or +
-send it more than once. The definition of complementary +
-modalities is less clear. The model +
-reflects a variety of different approaches to identify +
-groupings of channels based on criteria +
-found in other CMC theories as well as in perceptual +
-studies of media uses and gratifications +
-(Flanagin & Metzger, 2001), rather than on the +
-basis of some underlying functional property. It +
-clusters channels into the following groups: faceto-face, +
-mass media, oral media, or textual media. +
-Although a proposition refers to “maximizing +
-modalities through complementary successive +
-ICT use” (Stephens, 2007, p. 496), the theory +
-does not indicate what kind of combinations +
-among different ICT groups would be optimally +
-complementary. It may be that the use of two +
-nominally different ICTs constitutes sufficient +
-complementarity, although later propositions +
-address the superiority of mass media as an initial +
-medium and elsewhere the benefit of textbased +
-media for subsequent messages. +
-The ICT succession model received mixed +
-empirical support in a recent experiment +
-(Stephens & Rains, 2011). Research confederates +
-either e-mailed a persuasive message to participants +
-encouraging them to use the career services +
-center at their universities or read the message +
-face-to-face to the participant. A few minutes +
-later, based on the experimental condition, one  +
-470——PART IV: Processes and Functions +
-of several events transpired: (a) a confederate +
-then communicated a second message, with different +
-content, that also advocated using the +
-career services center, using either the same +
-channel (e-mail or face-to-face) as the first message +
-or the other of the two channels, or (b) a +
-confederate provided a message about a different +
-topic using one or other of the media combinations. +
-This experimental design allowed the +
-researchers to examine the influence of media +
-succession on outcomes independently of the +
-effect of the simple addition of more persuasive +
-arguments. Results revealed significantly greater +
-intention to use the career services center when +
-messages were conveyed using complementary +
-successive messages than when other message/ +
-media combinations were used, although attitudes +
-(rather than intentions), information +
-effectiveness perceptions, and recall did not differ +
-among the conditions as predicted. Complementary +
-media effects overrode the simple +
-effects of being exposed to multiple messages. +
-In one sense, the ICT succession theory offers +
-a modest digital-age update and elaboration to +
-conventional suggestions. As Koehler, Anatol, +
-and Applbaum wrote in their 1976 organizational +
-communication textbook, “We suggest +
-that a combination of oral and written (printed) +
-media are more effective in achieving employee +
-understanding than either oral or written messages +
-alone” (p. 204). The initial empirical +
-research compared two media that are rather +
-conventional by current standards, and despite +
-the Stephens and Rains (2011) article’s title +
-alluding to interpersonal interaction, no interpersonal +
-processes per se seem to have been +
-involved. Nevertheless, other aspects of the +
-researchers’ discussion of the model offer a +
-glimpse at research to come that may expand the +
-scope of the predictions beyond conventional +
-wisdom or first-generation Internet applications. +
-When the authors point out that “ICTs such as +
-mobile phones, e-mail, text messaging, and +
-instant messaging have made it increasingly possible +
-to communicate repeated messages over +
-time” (p. 102), they open the door to the discovery +
-of media selection strategies that may go well +
-beyond choices based on differences in the number +
-of code systems supported by different media. +
-How communication partners may choose +
-among many more options than simply just written +
-versus oral ones may be an interesting focus +
-of inquiry and illuminate much about communicators’ +
-literacies, opportunities, effort economies, +
-and communication strategies. These issues will +
-bear repeated attention across both organizational +
-and relational contexts such as the development +
-of friendships, courtship, maintenance, +
-conflict, and perhaps relational dissolution. The +
-issue of multimodality is addressed more fully +
-below, after some other concluding observations. +
-Challenges to CMC Research +
-This review ends with some notes of concern +
-about current trends in CMC research. These +
-concerns focus on three issues: (1) the increasing +
-neglect of off-line comparisons in CMC studies, +
-potentially undermining broad theoretical +
-understanding and leading to potentially inflated +
-views of CMC’s effects; (2) how and whether new +
-technologies affect the utility of theories that +
-were developed in the context of somewhat older +
-technological contexts; and (3) how we study +
-interpersonal communication when many relationships +
-are radically multimodal. +
-There appears to be an increasing tendency for +
-CMC research to focus on different features and +
-different users of CMC and not to make comparisons +
-with face-to-face communication or communication +
-using other traditional media. This trend +
-is supported by different disciplinary orientations +
-about what questions should concern us and by the +
-development of research tools that make CMC +
-much easier to analyze than its off-line counterpart. +
-For a number of years, many researchers have +
-extolled the end of the face-to-face “gold standard” +
-for CMC research (for a review, see Nardi & +
-Whittaker, 2002), meaning that online behavior +
-itself is a legitimate and significant focus of study +
-and that descriptions of it, or comparisons of different +
-interfaces or users, are sufficiently interesting +
-without having to compare observations of online  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——471 +
-to off-line behavior. Technology design research, +
-for example, may largely be uninformed by what +
-happens off-line, since its focus is on the discovery +
-of technology users’ needs and preferences and the +
-evaluation of technology features that optimally +
-address those criteria. +
-Additionally, there has been significant growth +
-in the development of low-cost computer programs +
-that provide powerful analyses of digitally +
-represented behavior. In particular, language +
-analysis programs that can be applied to large +
-corpuses of digital texts have made online behavior +
-more amenable to analysis and made textual +
-analysis far less onerous than it previously was. +
-The ease, cost, availability, and power of these +
-applications make them very appealing. At the +
-same time, their availability may privilege analysis +
-of the kind of digital primary data to which +
-the programs are especially well suited and facilitate +
-disregard for the analysis of analog face-toface +
-interaction recordings, which require +
-significant resources to transcribe and/or prepare +
-for digital analysis. +
-These factors, as well as others, may be promoting +
-the analysis of online interpersonal +
-behavior more frequently and of off-line behavior +
-less so. Although to many of us the dynamics +
-of organic online behavior are often quite interesting, +
-the lack of comparison with off-line +
-behaviors has the potential to lead to artificial +
-conclusions. We may infer support using native +
-digital sources for theoretically universal effects +
-when the effects are limited. We may likewise +
-conclude that certain behaviors are primarily or +
-exclusively the result of various qualities of +
-media, but without comparison with off-line +
-behavior that may exhibit similar patterns, such +
-conclusions may be fallacious and misleading. +
-Second, questions arise whether new technologies +
-should lead us to retire theories that +
-were developed in light of other, older technologies. +
-Good ways to ask these questions examine +
-the boundary conditions and scope of extant +
-theories. We should always assess how the topography +
-of new technologies’ features meet or +
-violate the assumptions of a theory. As discussed +
-above, theories that were premised on the lack of +
-visual information about one’s partners may not +
-hold as much utility for multimedia interfaces. +
-At the same time, advances in technologyenabled +
-social arrangements allow us to see if +
-theories can stretch their original assumptive +
-boundaries. Human and Lane (2008), for +
-instance, have appropriated elements of electronic +
-propinquity theory and the hyperpersonal +
-model to try to account for the idealization +
-that emerges through the online communication +
-that takes place between the occasional face-toface +
-meetings of geographically separated offline +
-relational partners. Exploring the degree to +
-which the processes implicated in older models +
-may be reconfigured for newer media presents +
-intriguing possibilities (as is demonstrably the +
-case with electronic propinquity theory). To the +
-extent that the older media’s boundary conditions +
-continue to appear within other, newer +
-systems, the vitality of the theories remains even +
-if the scope of their application declines. When +
-multimedia news stories or videos appear in a +
-Web 2.0 application but are accompanied by +
-user-generated comments appearing as anonymous, +
-plain-text messages, for example, theories +
-premised on unimodal media and focused on +
-anonymity remain quite potent with respect to +
-the effects of the comments. +
-Finally, just as the previous Handbook suggested +
-that relationships may develop through +
-multiple modalities (Walther & Parks, 2002), +
-many researchers have come to suggest that interpersonal +
-communication research must explicitly +
-recognize that contemporary relationships are +
-not conducted through one medium or another +
-but often through a great variety of channels. +
-Multimodality has become the primary channel +
-characteristic of interpersonal relationships: +
-We conduct our relationships face-to-face, +
-over the phone, and online through modes +
-as diverse as e-mail, instant messaging, +
-social network friending, personal messages, +
-comments, shared participation in +
-discussion forums and online games, and +
-the sharing of digital photos, music, and +
-videos. (Baym, 2009, p. 721) +
-472——PART IV: Processes and Functions +
-Research has yet to conceptualize what this means +
-for the study of relationships, except by reference to +
-media ecologies (e.g., Barnes, 2009), the implications +
-of which are not yet clear beyond phenomenological +
-levels. Even advocates of a multimodal +
-perspective at times do no more than survey individuals +
-about the use of all their Internet and +
-mobile applications and enter their total new technology +
-use as one undifferentiated predictor variable +
-comparing new technology, old media, and +
-face-to-face interaction on relational outcomes of +
-some kind. In contrast, other researchers have +
-advanced good questions based on established +
-theories applied to new media to describe and +
-explain the disappointing effects of moving a new +
-relationship from online to off-line and back (e.g., +
-Ramirez & Wang, 2008; Ramirez & Zhang, 2007). +
-We will need new theoretical concepts with +
-which to describe the functional attributes of +
-groups of technologies. Qualities such as the +
-opportunistic availability of different media (e.g., +
-texting or mobile-enabled microblogging) may +
-be such a concept. Economy of effort may be a +
-useful property with which to describe social +
-media that allow one to contribute to the maintenance +
-of numerous relationships with a single +
-message. Knowing which applications provide +
-asymmetrical interpersonal information-seeking +
-(I can Google you without you knowing it) or +
-symmetrical requirements (You have to grant me +
-access to your Facebook profile before you can +
-see mine) may be a useful frame, depending on +
-the theoretical questions these phenomena +
-arouse. It is also likely that different media are +
-used in functional, strategic sequences (beyond +
-repetition) that may illuminate relational patterns. +
-Our chapter in the previous Handbook +
-quoted Mitchell (1995): “Hacker lore has it that +
-burgeoning cyberspace romances progress +
-through broadening bandwidth and multiplying +
-modalities—from exchange of e-mail to phone +
-and photo, then taking the big step of going +
-(face-to-face), then climbing into bed” (p. 19). +
-Lore aside, technology sequences and their relational +
-significance deserve an update: If a man +
-takes an interest in a woman he sees in a class, he +
-may want to scan the Web for information about +
-her. If that search suggests potential reward, he +
-may talk to her to establish a minimal basis of +
-familiarity so that he can request access to her +
-social network profile and be able to see how +
-many friends she has, what they look like, what +
-their comments have to say about her, and how +
-she interacts with them in turn. If results are +
-encouraging, a face-to-face conversation may +
-come next, followed by a reinforcing e-mail or +
-social network posting. Do increases in channel +
-access signify relational escalation? Do we meet +
-new partners’ Flickr family photo collection +
-before we meet the parents, and why? Rather +
-than resign ourselves to undifferentiated, massive +
-multimodality, future research may begin to contemplate +
-the strategic and interpersonal signification +
-possibilities it presents as its users exploit +
-the vast relational potentials of CMC. +
-References +
-Amichai-Hamburger, Y. (Ed.). (2005). The social net: +
-Understanding human behavior in cyberspace. +
-Oxford, UK: Oxford University Press. +
-Amichai-Hamburger, Y. (2007). Personality, individual +
-differences and Internet use. In A. Joinson, +
-K. McKenna, T. Postmes, & U.-D. Reips (Eds.), +
-The Oxford handbook of Internet psychology +
-(pp. 187–204). Oxford, UK: Oxford University +
-Press. +
-Antheunis, M. L., Valkenburg, P. M., & Peter, J. (2007). +
-Computer-mediated communication and interpersonal +
-attraction: An experimental test of +
-two explanatory hypotheses. CyberPsychology & +
-Behavior, 10, 831–835. +
-Antheunis, M. L., Valkenburg, P. M., & Peter, J. (2010). +
-Getting acquainted through social network sites: +
-Testing a model of online uncertainty reduction +
-and social attraction. Computers in Human +
-Behavior, 26, 100–109. +
-Baker, S. C., Wentz, R. K., & Woods, M. M. (2009). Using +
-virtual worlds in education: Second life as an educational +
-tool. Teaching of Psychology, 36, 59–64. +
-Barnes, S. B. (2009). Relationship networking: Society +
-and education. Journal of Computer-Mediated Communication, +
-14, 735–742. +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——473 +
-Baym, N. K. (2009). A call for grounding in the face +
-of blurred boundaries. Journal of ComputerMediated +
-Communication, 14, 720–723. +
-Baym, N. K. (2010). Personal connections in the digital +
-age. Cambridge, UK: Polity Press. +
-Bente, G., Rüggenberg, S., Krämer, N. C., & Eschenburg, F. +
-(2008). Avatar-mediated networking: Increasing +
-social presence and interpersonal trust in net-based +
-collaborations. Human Communication Research, +
-34, 287–318. +
-Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward +
-a more robust theory and measure of social presence: +
-Review and suggested criteria. Presence: Teleoperators +
-and Virtual Environments, 12, 456–480. +
-boyd, d. (2007). Why youth ♥ social network sites: The +
-role of networked publics in teenage social life. In +
-D. Buckingham (Ed.) Youth, identity, and digital +
-media (pp. 119–142). Cambridge: MIT Press. +
-Burgoon, J. K., & Le Poire, B. A. (1993). Effects of communication +
-expectancies, actual communication, +
-and expectancy disconfirmation on evaluations of +
-communicators and their communication behavior. +
-Human Communication Research, 20, 67–96. +
-Caplan, S. E. (2003). Preference for online social interaction: +
-A theory of problematic Internet use and +
-psychosocial well-being. Communication Research, +
-30, 625–648. +
-Caplan, S. E. (2005). A social skill account of problematic +
-Internet use. Journal of Communication, 55, +
-721–736. +
-Carlson, J. R., & Zmud, R. W. (1994). Channel expansion +
-theory: A dynamic view of media and information +
-richness perceptions. In D. P. Moore (Ed.), +
-Academy of Management: Best papers proceedings +
-1994 (pp. 280–284). Madison, WI: Omnipress. +
-Carlson, J. R., & Zmud, R. W. (1999). Channel expansion +
-theory and the experiential nature of media +
-richness perceptions. Academy of Management +
-Journal, 42, 153–170. +
-Childress, M. D., & Braswell, R. (2006). Using massively +
-multiplayer online role-playing games for +
-online learning. Distance Education, 27, 187–196. +
-Collins, N. L., & Miller, L. C. (1994). Self-disclosure +
-and liking: A meta-analytic review. Psychological +
-Bulletin, 116, 457–475. +
-Culnan, M. J., & Markus, M. L. (1987). Information +
-technologies. In F. M. Jablin, L. L. Putnam, +
-K. H. Roberts, & L. W. Porter (Eds.), Handbook of +
-organizational communication: An interdisciplinary +
-perspective (pp. 420–443). Newbury Park, CA: Sage. +
-Cummings, J. M., Lee, J. B., & Kraut, R. E. (2006). +
-Communication technology and friendship during +
-the transition from high school to college. In +
-R. E. Kraut, M. Brynin, & S. Kiesler (Eds.), +
-Computers, phones, and the Internet: Domesticating +
-information technology (pp. 265–278). New York: +
-Oxford University Press. +
-Daft, R. L., & Lengel, R. H. (1984). Information richness: +
-A new approach to managerial behavior +
-and organization design. In B. M. Staw & +
-L. L. Cummings (Eds.), Research in organizational +
-behavior (Vol. 6, pp. 191–233). Greenwich, CT: +
-JAI Press. +
-Daft, R. L., & Lengel, R. H. (1986). Organizational +
-information requirements, media richness and +
-structural design. Management Science, 32, 554–571. +
-Daft, R. L., Lengel, R. H., & Trevino, L. K. (1987). +
-Message equivocality, media selection, and manager +
-performance: Implications for information +
-systems. MIS Quarterly, 11, 355–368. +
-DeAndrea, D. C., & Walther, J. B. (in press). Attributions +
-for inconsistencies between online and offline +
-self-presentations. Communication Research. +
-Dennis, A. R., & Kinney, S. T. (1998). Testing media +
-richness theory in the new media: The effects of +
-cues, feedback, and task equivocality. Information +
-Systems Research, 9, 256–274. +
-Derks, D., Bos, A. E. R., & von Grumbkow, J. (2007). +
-Emoticons and social interaction on the Internet: +
-The importance of social context. Computers in +
-Human Behavior, 23, 842–849. +
-Di Blasio, P., & Milani, L. (2008). Computer-mediated +
-communication and persuasion: Peripheral vs. central +
-routes to opinion shift. Computers in Human +
-Behavior, 24, 798–815. +
-Donath, J. (1999). Identity and deception in the virtual +
-community. In M. A. Smith & P. Kollock (Eds.), +
-Communities in cyberspace (pp. 29–59). New York: +
-Routledge. +
-Donath, J. (2007). Signals in social supernets. Journal +
-of Computer-Mediated Communication, 13(1), +
-Article 12. Retrieved January 20, 2008, from http:// +
-jcmc.indiana.edu/vol13/issue1/donath.html +
-Douglas, K. M., & McGarty, C. (2001). Identifiability +
-and self-presentation: Computer-mediated communication +
-and intergroup interaction. British +
-Journal of Social Psychology, 40, 399–416. +
-Duck, S., Rutt, D. J., Hurst, M. H., & Strejc, H. (1991). +
-Some evident truths about conversations in +
-everyday relationships: All communications are  +
-474——PART IV: Processes and Functions +
-not created equal. Human Communication Research, +
-18, 228–267. +
-D’Urso, S. C., & Rains, S. A. (2008). Examining the +
-scope of channel expansion: A test of channel +
-expansion theory with new and traditional communication +
-media. Management Communication +
-Quarterly, 21, 486–507. +
-Ellison, N. B., Heino, R. D., & Gibbs, J. L. (2006). +
-Managing impressions online: Self-presentation +
-processes in the online dating environment. +
-Journal of Computer-Mediated Communication, +
-11(2), Article 2. Retrieved January 30, 2007, from +
-http://jcmc.indiana.edu/vol11/issue2/ellison.html +
-Epley, N., & Kruger, J. (2005). What you type isn’t what +
-they read: The perseverance of stereotypes and +
-expectancies over e-mail. Journal of Experimental +
-Social Psychology, 41, 414–422. +
-Flanagin, A. J., & Metzger, M. J. (2001). Internet use in +
-the contemporary media environment. Human +
-Communication Research, 27, 153–181. +
-Foulger, D. A. (1990). Medium as process: The structure, +
-use, and practice of computer conferencing on IBM’s +
-IBMPC computer conferencing facility. Unpublished +
-doctoral dissertation, Temple University, +
-Pennsylvania. +
-Fulk, J., & Gould, J. J. (2009). Features and contexts +
-in technology research: A modest proposal for +
-research and reporting. Journal of ComputerMediated +
-Communication, 14, 764–770. +
-Fulk, J., Schmitz, J., & Ryu, D. (1995). Cognitive elements +
-in the social construction of communication +
-technology. Management Communication Quarterly, +
-8, 259–288. +
-Fulk, J., Schmitz, J., & Steinfield, C. (1990). A social influence +
-model of technology use. In J. Fulk & +
-C. Steinfeld (Eds.), Organizations and communication +
-technology (pp. 71–94). Newbury Park, CA: Sage. +
-Fulk, J., Steinfield, C., Schmitz, J., & Power, J. G. (1987). +
-A social information processing model of media +
-use in organizations. Communication Research, +
-14(5), 529–552. +
-Galagher, J., & Kraut, R. E. (1994). Computer-mediated +
-communication for intellectual teamwork: An +
-experiment in group writing. Information Systems +
-Research, 5, 110–138. +
-Gibbs, J. L., Ellison, N. B., & Heino, R. D. (2006). Selfpresentation +
-in online personals: The role of +
-anticipated future interaction, self-disclosure, and +
-perceived success in Internet dating. Communication +
-Research, 33, 1–26. +
-Gonzales, A. L., & Hancock, J. T. (2008). Identity shift +
-in computer-mediated environments. Media Psychology, +
-11, 167–185. +
-Guadagno, R. E., & Cialdini, R. B. (2002). Online persuasion: +
-An examination of gender differences in +
-computer-mediated interpersonal influence. Group +
-Dynamics: Theory Research and Practice, 6, 38–51. +
-Guadagno, R. E., & Cialdini, R. B. (2007). Persuade +
-him by email, but see her in person: Online persuasion +
-revisited. Computers in Human Behavior, +
-23, 999–1015. +
-Gunawardena, C. N. (2004). Designing the social environment +
-for online learning: The role of social +
-presence. In D. Murphy, R. Carr, J. Taylor, & +
-T. Wong (Eds.), Distance education and technology: +
-Issues and practice (pp. 255–270). Hong Kong: +
-Open University of Hong Kong Press. +
-Hall, E. T. (1976). Beyond culture. New York: Doubleday. +
-Hall, J. A., Park, N., Song, H., & Cody, M. J. (2010). +
-Strategic misrepresentation in online dating: The +
-effects of gender, self-monitoring, and personality +
-traits. Journal of Social and Personal Relations, +
-27, 117–135. +
-Hancock, J. T., Thom-Santelli, J., & Ritchie, T. (2004). +
-Deception and design: The impact of communication +
-technologies on lying behavior. In +
-E. Dykstra-Erickson & M. Tscheligi (Eds.), Proceedings +
-of the ACM Conference on Human +
-Factors in Computing Systems (CHI 2004, Vol. 6, +
-pp. 130–136). New York: ACM. +
-Hancock, J. T., & Toma, C. L. (2009). Putting your best +
-face forward: The accuracy of online dating photographs. +
-Journal of Communication, 59, 367–386. +
-Heino, R. D., Ellison, N. B., & Gibbs, J. L. (2010). +
-Relationshopping: Investigating the market metaphor +
-in online dating. Journal of Social and +
-Personal Relationships, 27, 427–447. +
-Hian, L. B., Chuan, S. L., Trevor, T. M. K., & Detenber, +
-B. H. (2004). Getting to know you: Exploring the +
-development of relational intimacy in computermediated +
-communication. Journal of ComputerMediated +
-Communication, 9(3). Retrieved January +
-3, 2007, from http://jcmc.indiana.edu/vol9/issue3/ +
-detenber.html +
-Hiltz, S. R., Johnson, K., & Agle, G. (1978). Replicating +
-Bales’ problem solving experiments on a computerized +
-conference: A pilot study (Research Report +
-No. 8). Newark, NJ: New Jersey Institute of Technology, +
-Computerized Conferencing and Communications +
-Center. +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——475 +
-Human, R., & Lane, D. (2008, November). Virtually +
-friends in cyberspace: Explaining the migration +
-from FtF to CMC relationships with electronic +
-functional propinquity theory. Paper presented at +
-the annual meeting of the National Communication +
-Association, San Diego, CA. +
-Ickes, W., Patterson, M. L., Rajecki, D. W., & Tanford, S. +
-(1982). Behavioral and cognitive consequences +
-of reciprocal versus compensatory responses to +
-pre-interaction expectancies. Social Cognition, 1, +
-160–190. +
-Jacobson, D. (1999). Impression formation in cyberspace: +
-Online expectations and offline experiences +
-in text-based virtual communities. Journal of +
-Computer-Mediated Communication, 5(1). Retrieved +
-March 31, 2011, from http://jcmc.indiana.edu/ +
-vol5/issue1/jacobson.html +
-Jiang, C. L., Bazarova, N. N., & Hancock, J. T. (2011). The +
-disclosure-intimacy link in computer-mediated +
-communication: An attributional extension of +
-the hyperpersonal model. Human Communication +
-Research, 37, 58–77. +
-Joinson, A. N. (2001). Self-disclosure in computermediated +
-communication: The role of self-awareness +
-and visual anonymity. European Journal of Social +
-Psychology, 31, 177–192. +
-Joinson, A., McKenna, K., Postmes, T., & Reips, U.-D. +
-(Eds.). (2007). The Oxford handbook of Internet +
-psychology. Oxford, UK: Oxford University Press. +
-Katz, J. E., & Rice, R. E. (2002). Social consequences of +
-Internet use: Access, involvement, and interaction. +
-Cambridge: MIT Press. +
-Kelly, J. R., & McGrath, J. E. (1985). Effects of time +
-limits and task types on task performance and +
-interaction of four-person groups. Journal of Personality +
-and Social Psychology, 49, 395–407. +
-Kenny, D. A. (1994). Interpersonal perception: A social +
-relations analysis. New York: Guilford Press. +
-Kim, J., & Dindia, K. (2011). Online self-disclosure: A +
-review of research. In K. B. Wright & L. M. Webb +
-(Eds.), Computer-mediated communication in personal +
-relationships (pp. 156–181). New York: Peter +
-Lang. +
-Klimmt, C., & Hartmann, T. (2008). Mediated interpersonal +
-communication in multiplayer videogames: +
-Implications for entertainment and +
-relationship management. In E. A. Konijn, S. Utz, +
-M. Tanis, & S. B. Barnes (Eds.), Mediated interpersonal +
-communication (pp. 309–330). New York: +
-Routledge. +
-Koehler, J. W., Anatol, K. W. E., & Applbaum, R. L. +
-(1976). Organizational communication: Behavioral +
-perspectives. New York: Holt, Rinehart, & Winston. +
-Konijn, E. A., Utz, S., Tanis, M., & Barnes, S. B. (Eds.). +
-(2008). Mediated interpersonal communication. +
-New York: Routledge. +
-Korzenny, F. (1978). A theory of electronic propinquity: +
-Mediated communication in organizations. +
-Communication Research, 5, 3–24. +
-Korzenny, F., & Bauer, C. (1981). Testing the theory of +
-electronic propinquity. Communication Research, +
-8, 479–498. +
-Labi, N. (2007, September). An IM infatuation turned +
-to romance. Then the truth came out. WIRED, +
-15(9), 149–153. +
-Lawson, H. M., & Leck, K. (2006). Dynamics of Internet +
-dating. Social Science Computer Review, 24, 189–208. +
-Lea, M., & Spears, R. (1992). Paralanguage and social +
-perception in computer-mediated communication. +
-Journal of Organizational Computing, 2, +
-321–341. +
-Lea, M., & Spears, R. (1995). Love at first byte? +
-Building personal relationships over computer +
-networks. In J. T. Wood & S. Duck (Eds.), +
-Understudied relationships: Off the beaten track +
-(pp. 197–233). Thousand Oaks, CA: Sage. +
-Lea, M., Spears, R., & de Groot, D. (2001). Knowing +
-me, knowing you: Anonymity effects on social +
-identity processes within groups. Personality and +
-Social Psychology Bulletin, 27, 526–537. +
-Lee, E.-J. (2004). Effects of visual representation on social +
-influence in computer-mediated communication. +
-Human Communication Research, 30, 234–259. +
-Lee, K. M. (2004). Presence, explicated. Communication +
-Theory, 14, 27–50. +
-Lombard, M., & Ditton, T. (1997). At the heart of it all: +
-The concept of presence. Journal of ComputerMediated +
-Communication, 3(2). Retrieved March 9, +
-1999, from http://jcmc.indiana.edu/vol3/issue2/ +
-lombard.html +
-Markey, P. M., & Wells, S. M. (2002). Interpersonal perception +
-in Internet chat rooms. Journal of Research +
-in Personality, 36, 134–146. +
-Markus, M. L. (1994). Electronic mail as the medium of +
-managerial choice. Organization Science, 5, 502–527. +
-Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & +
-McCann, R. M. (2003). Credibility for the 21st +
-century: Integrating perspectives on source, message, +
-and media credibility in the contemporary +
-media environment. In P. J. Kalbfleisch (Ed.),  +
-476——PART IV: Processes and Functions +
-Communication yearbook 27 (pp. 293–335). New +
-York: Routledge. +
-Mitchell, W. J. (1995). City of bits: Space, place, and the +
-infobahn. Cambridge: MIT Press. +
-Monge, P. R. (1980). Multivariate multiple regression. +
-In P. R. Monge & J. N. Cappella (Eds.), Multivariate +
-techniques in human communication research +
-pp. 13–56. New York: Academic Press. +
-Nardi, B., & Whittaker, S. (2002). The place of face +
-to face communication in distributed work. In +
-P. J. Hinds & S. Kiesler (Eds.), Distributed work: +
-New research on working across distance using +
-technology (pp. 83–110). Cambridge: MIT Press. +
-Nowak, K., Watt, J. H., & Walther, J. (2005). The influence +
-of synchrony and sensory modality on the +
-person perception process in computer mediated +
-groups. Journal of Computer-Mediated Communication, +
-10 (3). Retrieved February 1, 2006, from +
-http://jcmc.indiana.edu/vol10/issue3/nowak.html +
-Nowak, K., Watt, J. H., & Walther, J. B. (2009). +
-Computer mediated teamwork and the efficiency +
-framework: Exploring the influence of synchrony +
-and cues on media satisfaction and outcome success. +
-Computers in Human Behavior, 25, 1108–1119. +
-Nowak, K. L., & Biocca, F. (2003). The effect of the +
-agency and anthropomorphism on users’ sense of +
-telepresence, copresence, and social presence in +
-virtual environments. Presence: Teleoperators and +
-Virtual Environments, 12, 481–494. +
-Oren, A., Mioduser, D., & Nachmias, R. (2002). The +
-development of social climate in virtual learning +
-discussion groups. International Review of Research +
-in Open and Distance Learning, 3(1), 1–19. +
-Papacharissi, Z. (Ed.). (2010). A networked self: Identity, +
-community and culture on social network sites. +
-New York: Routledge. +
-Parks, M. R., & Floyd, K. (1996). Making friends in +
-cyberspace. Journal of Communication, 40, 80–97. +
-Parks, M. R., & Roberts, L. (1998). Making MOOsic: The +
-development of personal relationships on line and +
-a comparison to their off-line counterparts. Journal +
-of Social and Personal Relationships, 15, 517–537. +
-Peña, J., & Hancock, J. T. (2006). An analysis of socioemotional +
-and task-oriented communication in +
-an online multiplayer video game. Communication +
-Research, 33, 92–109. +
-Peter, J., Valkenburg, P. M., & Schouten, A. P. (2005). +
-Developing a model of adolescent friendship formation +
-on the Internet. Cyberpsychology & Behavior, +
-8, 423–430. +
-Petty, R. E., & Cacioppo, J. T. (1986). The elaboration +
-likelihood model of persuasion. Advances in +
-Experimental Social Psychology, 19, 123–205. +
-Postmes, T., Baray, G., Haslam, S. A., Morton, T., & +
-Swaab, R. (2006). The dynamics of personal and +
-social identity formation. In T. Postmes & J. Jetten +
-(Eds.), Individuality and the group: Advances in +
-social identity (pp. 215–236). London: Sage. +
-Postmes, T., & Baym, N. (2005). Intergroup dimensions +
-of Internet. In J. Harwood & H. Giles (Eds.), +
-Intergroup communication: Multiple perspectives +
-(pp. 213–238). New York: Peter Lang. +
-Postmes, T., Spears, R., Lee, A. T., & Novak, R. J. (2005). +
-Individuality and social influence in groups: +
-Inductive and deductive routes to group identity. +
-Journal of Personality and Social Psychology, 89, +
-747–763. +
-Rains, S. A., & Scott, C. R. (2007). To identify or not to +
-identify: A theoretical model of receiver responses +
-to anonymous communication. Communication +
-Theory, 17, 61–91. +
-Ramirez, A., Jr., & Wang, Z. (2008). When online meets +
-offline: An expectancy violation theory perspective +
-on modality switching. Journal of Communication, +
-58, 20–39. +
-Ramirez, A., Jr., & Zhang, S. (2007). When online +
-meets offline: The effect of modality switching on +
-relational communication. Communication Monographs, +
-74, 287–310. +
-Ramirez, A., Jr., Zhang, S., McGrew, K., & Lin, S.-F. +
-(2007). Relational communication in computermediated +
-interaction: A comparison of participantobserver +
-perspectives. Communication Monographs, +
-74, 492–516. +
-Rau, P.-L. P., Peng, S.-Y., & Yang, C.-C. (2006). Time +
-distortion for expert and novice online game +
-players. CyberPsychology & Behavior, 9, 396–403. +
-Reicher, S. D., Spears, R., & Postmes, T. (1995). A +
-social identity model of deindividuation phenomena. +
-European Review of Social Psychology, +
-6, 161–198. +
-Rice, R. E., & Case, D. (1983). Electronic message systems +
-in the University: A description of use and +
-utility. Journal of Communication, 33(1), 131–152. +
-Roberts, L. D., Smith, L. M., & Pollock, C. (1996, +
-September). A model of social interaction via +
-computer-mediated communication in real-time +
-text-based virtual environments. Paper presented +
-at the meeting of the Australian Psychological +
-Society, Sydney, New South Wales, Australia. +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——477 +
-Rogers, P., & Lea, M. (2004). Cohesion in online +
-groups. In K. Morgan, C. A. Brebbia, J. Sanchez, & +
-A. Voiskounsky (Eds), Human perspectives in the +
-Internet society: Culture, psychology and gender +
-(pp.115–124). Southampton, UK: WIT Press. +
-Sackett, A. M., Nelson, L. D., Meyvis, T., Converse, B. A., +
-& Sackett, A. L. (2009). You’re having fun when +
-time flies: The hedonic consequences of subjective +
-time progression. Psychological Science, 21, 111–117. +
-Sanders, R. E. (1997). Find your partner and do-si-do: +
-The formation of personal relationships between +
-social beings. Journal of Social and Personal Relationships, +
-14, 387–415. +
-Schouten, A. P., Valkenburg, P. M., & Peter, J. (2007). +
-Precursors and underlying processes of adolescents’ +
-online self-disclosure: Developing and testing +
-an “Internet-attribute-perception” model. Media +
-Psychology, 10, 292–315. +
-Scott, C. R. (2009). A whole-hearted effort to get it +
-half right: Predicting the future of communication +
-technology scholarship. Journal of ComputerMediated +
-Communication, 14, 753–757. +
-Setlock, L. D., Quinones, P.-A., & Fussell, S. R. (2007). +
-Does culture interact with media richness? The +
-effects of audio vs. video conferencing on Chinese +
-and American dyads. In Proceedings of the 40th +
-annual Hawaii International Conference on System +
-Sciences. Retrieved September 1, 2009, from http:// +
-csdl2.computer.org/comp/proceedings/hicss/2007/ +
-2755/00/27550013.pdf +
-Short, J., Williams, E., & Christie, B. (1976). The social +
-psychology of telecommunications. London: Wiley. +
-Siegel, J., Dubrovsky, V., Kiesler, S., & Mcguire, T. W. +
-(1986). Group processes in computer-mediated +
-communication. Organizational Behavior and +
-Human Decision Processes, 37, 157–187. +
-Snyder, M., Tanke, E. D., & Berscheid, E. (1977). Social +
-perception and interpersonal behavior: On the +
-self-fulfilling nature of social stereotypes. Journal +
-of Experimental Social Psychology, 35, 656–666. +
-Sproull, L., & Faraj, S. (1997). Atheism, sex, and databases: +
-The Net as a social technology. In S. Kiesler +
-(Ed.), Cultures of the Internet (pp. 35–51). Mahwah, +
-NJ: Lawrence Erlbaum. +
-Sproull, L., & Kiesler, S. (1986). Reducing social context +
-cues: Electronic mail in organizational communication. +
-Management Science, 32, 1492–1512. +
-Stephens, K. K. (2007). The successive use of information +
-and communication technologies at work. +
-Communication Theory, 17, 486–507. +
-Stephens, K. K., & Rains, S. A. (2011). Information and +
-communication technology sequences and message +
-repetition in interpersonal interaction. Communication +
-Research, 38, 101–122. +
-Stone, A. R. (1995). The war of desire and technology +
-at the close of the mechanical age. Cambridge: MIT +
-Press. +
-Sundar, S. S. (2008). The MAIN model: A heuristic +
-approach to understanding technology effects on +
-credibility. In M. J. Metzger & A. J. Flanagin (Eds.), +
-Digital media, youth, and credibility (pp. 73–100). +
-Cambridge: MIT Press. +
-Tajfel, H. (1978). Differentiation between social groups: +
-Studies in the social psychology of intergroup relations. +
-London: Academic Press. +
-Tajfel, H., & Turner, J. C. (1979). An integrative theory +
-of intergroup conflict. In W. Austin & S. Worchel +
-(Eds.), The social psychology of intergroup relations +
-(pp. 33–47). Monterey, CA: Brooks/Cole. +
-Tanis, M., & Postmes, T. (2003). Social cues and impression +
-formation in CMC. Journal of Communication, +
-53, 676–693. +
-Tidwell, L. C., & Walther, J. B. (2002). Computermediated +
-communication effects on disclosure, +
-impressions, and interpersonal evaluations: Getting +
-to know one another a bit at a time. Human +
-Communication Research, 28, 317–348. +
-Toma, C. L., Hancock, J. T., & Ellison, N. B. (2008). +
-Separating fact from fiction: An examination of +
-deceptive self-presentation in online dating profiles. +
-Personality and Social Psychology Bulletin, +
-34, 1023–1036. +
-Tong, S. T., Van Der Heide, B., Langwell, L., & Walther, +
-J. B. (2008). Too much of a good thing? The +
-relationship between number of friends and +
-interpersonal impressions on Facebook. Journal of +
-Computer-Mediated Communication, 13, 531–549. +
-Tong, S. T., & Walther, J. B. (2011b). Relational maintenance +
-and computer-mediated communication. +
-In K. B. Wright & L. M. Webb (Eds.), Computermediated +
-communication in personal relationships +
-(pp. 98–119). New York: Peter Lang. +
-Tong, S. T., & Walther, J. B. (2011a). Just say “No +
-thanks”: Romantic rejection in computer-mediated +
-communication. Journal of Social and Personal +
-Relationships 28, 488–506. +
-Utz, S. (2010). Show me your friends and I will tell you +
-what type of person you are: How one’s profile, +
-number of friends, and type of friends influence +
-impression formation on social network sites.  +
-478——PART IV: Processes and Functions +
-Journal of Computer-Mediated Communication, +
-15, 314–335. +
-Valkenburg, P. M., & Peter, J. (2009). Social consequences +
-of the Internet for adolescents: A decade +
-of research. Current Directions in Psychological +
-Science, 15, 1–5. +
-Van Der Heide, B. (2008, May). Persuasion on the ‘net: +
-A synthetic propositional framework. Paper presented +
-at the annual meeting of the International +
-Communication Association, Montreal, Quebec, +
-Canada. +
-Van Gelder, L. (1996). The strange case of the electronic +
-lover. In C. Dunlop & R. Kling (Eds.), Computerization +
-and controversy: Value conflicts and +
-social choices (pp. 533–547). Boston: Academic +
-Press. +
-Walther, J. B. (1992). Interpersonal effects in computer-mediated +
-interaction: A relational perspective. +
-Communication Research, 19, 52–90. +
-Walther, J. B. (1996). Computer-mediated communication: +
-Impersonal, interpersonal, and hyperpersonal +
-interaction. Communication Research, 23, 3–43. +
-Walther, J. B. (2006). Nonverbal dynamics in computermediated +
-communication, or :( and the net :(’s +
-with you, :) and you :) alone. In V. Manusov & +
-M. L. Patterson (Eds.), Handbook of nonverbal +
-communication (pp. 461–479). Thousand Oaks, +
-CA: Sage. +
-Walther, J. B. (2007). Selective self-presentation in +
-computer-mediated communication: Hyperpersonal +
-dimensions of technology, language, and +
-cognition. Computers in Human Behavior, 23, +
-2538–2557. +
-Walther, J. B. (2009). Theories, boundaries, and all of +
-the above. Journal of Computer-Mediated Communication, +
-14, 748–752. +
-Walther, J. B. (2010). Computer-mediated communication. +
-In C. R. Berger, M. E. Roloff, & D. R. RoskosEwoldsen +
-(Eds.), Handbook of communication science +
-(2nd ed., pp. 489–505). Thousand Oaks: Sage. +
-Walther, J. B., & Bazarova, N. (2008). Validation and +
-application of electronic propinquity theory to +
-computer-mediated communication in groups. +
-Communication Research, 35, 622–645. +
-Walther, J. B., & Carr, C. T. (2010). Internet interaction +
-and intergroup dynamics: Problems and solutions +
-in computer-mediated communication. In +
-H. Giles, S. Reid, & J. Harwood (Eds.), The dynamics +
-of intergroup communication (pp. 209–220). +
-New York: Peter Lang. +
-Walther, J. B., DeAndrea, D., Kim, J., & Anthony, J. (2010). +
-The influence of online comments on perceptions +
-of anti-marijuana public service announcements +
-on YouTube. Human Communication Research, 36, +
-469–492. +
-Walther, J. B., DeAndrea, D. C., & Tong, S. T. (2010). +
-Computer-mediated communication versus +
-vocal communication in the amelioration of preinteraction +
-stereotypes: An examination of theories, +
-assumptions, and methods in mediated communication +
-research. Media Psychology, 13, 364–386. +
-Walther, J. B., Liang, Y., DeAndrea, D. C., Tong, S. T., +
-Carr, C. T., Spottswood, E. L., et al. (2011). The +
-effect of feedback on identity shift in computermediated +
-communication. Media Psychology, 14, +
-1–26. +
-Walther, J. B., Loh, T., & Granka, L. (2005). Let me +
-count the ways: The interchange of verbal and +
-nonverbal cues in computer-mediated and faceto-face +
-affinity. Journal of Language and Social +
-Psychology, 24, 36–65. +
-Walther, J. B., & Parks, M. R. (2002). Cues filtered +
-out, cues filtered in: Computer-mediated communication +
-and relationships. In M. L. Knapp & +
-J. A. Daly (Eds.), Handbook of interpersonal communication +
-(3rd ed., pp. 529–563). Thousand +
-Oaks, CA: Sage. +
-Walther, J. B., Van Der Heide, B., Hamel, L., & +
-Shulman, H. (2009). Self-generated versus othergenerated +
-statements and impressions in computermediated +
-communication: A test of warranting +
-theory using Facebook. Communication Research, +
-36, 229–253. +
-Walther, J. B., Van Der Heide, B., Tong, S. T., Carr, C. T., +
-& Atkin, C. K. (2010). The effects of interpersonal +
-goals on inadvertent intrapersonal influence in +
-computer-mediated communication. Human +
-Communication Research, 36, 323–347. +
-Wang, Z. (2007, November). Interpersonal and group +
-level measures in attraction and group identification: +
-A factor analysis approach. Paper presented +
-at the annual meeting of the National Communication +
-Association, Chicago. +
-Wang, Z., Walther, J. B., & Hancock, J. T. (2009). Social +
-identification and interpersonal communication +
-in computer-mediated communication: What you +
-do versus who you are in virtual groups. Human +
-Communication Research, 35, 59–85. +
-Warkentin, D., Woodworth, M., Hancock, J. T., & +
-Cormier, N. (2010). Warrants and deception in  +
-Chapter 14: Computer-Mediated Communication and Interpersonal Relations——479 +
-computer-mediated communication. In K. Inkpen +
-& C. Gutwin (Eds.), Proceedings of the 2010 ACM +
-Conference on Computer Supported Cooperative +
-Work (pp. 9–12). New York: ACM. +
-Westerman, D. K., Van Der Heide, B., Klein, K. A., & +
-Walther, J. B. (2008). How do people really seek +
-information about others? Information seeking +
-across Internet and traditional communication +
-sources. Journal of Computer-Mediated Communication, +
-13, 751–767. +
-Whitty, M. (2008). Revealing the “real” me, searching +
-for the “actual” you: Presentations of self on an +
-Internet dating site. Computers in Human Behavior, +
-24, 1707–1723. +
-Whitty, M., & Carr, A. (2006). Cyberspace romance: The +
-psychology of online relationships. New York: Palgrave +
-MacMillan. +
-Wilson, J. M., Straus, S. G., & McEvily, W. J. (2006). +
-All in due time: The development of trust in +
-computer-mediated and face-to-face groups. +
-Organizational Behavior and Human Decision +
-Processes, 99, 16–33. +
-Wright, K. B., & Webb, L. M. (Eds.). (2011). Computermediated +
-communication in personal relationships. +
-New York: Peter Lang. +
-Yzer, M. C., & Southwell, B. G. (2008). New communication +
-technologies, old questions. American +
-Behavioral Scientist, 25, 8–20.+
theories_of_computer_mediated_communication_and_interpersonal_relations.1492392270.txt.gz · Last modified: 2017/04/17 09:54 by hkimscil
Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki