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+See [[http://www.sagepub.com/upm-data/42241_14.pdf|Theories of Computer-Mediated Communication and Interpersonal Relations]]
 {{:42241_14.pdf|Theories of Computer-Mediated Communication and Interpersonal Relations}}
-CHAPTER 14
-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
-——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
-——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,
-; 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,
-). 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
-——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,
-; 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
-——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,
-). 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
-——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,
-). 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
-——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,
-) 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,
-; 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”
-——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,
-), 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,
-, 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
-——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
-——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,
-). 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,
-; 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
-——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.,
-) 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,
-; 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
-——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,
-; 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.,
-). 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,
-; 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,
-), 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
-——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,
-). 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.,
-). 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
-——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,
-, 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.,
-). 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
-——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)
-——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.
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