====== Theory ======
* Social Identity Theory
* Self-categorization Theory
Three Perspectives on Relating Online
^ Perspective ^ Claim ^ Relationships ^
| Impersonal | The lack of cues limits \\ the quality of interaction. | Relationships are unlikely to \\ emerge in CMC. |
| Interpersonal | Learned behaviors can help \\ compensate for the lack of cues | Relationships can emerge \\ in CMC |
| Hyperpersonal | The lack of nonverbal \\ discriminators actually helps \\ some find their voice | For some, the ability to relate \\ is more substantial in CMC |
* Wood, Andrew F. and Matthew J. Smith. Online Communication: Linking Technology, Identity, and Culture. Second Edition. Lawrence Erlbaum Associates, 2005. Chapter 4, “Relating Online” (78-100) {{:Online Communication Linking Technology Identity and Cult 2005.pdf|PDF}}
* According to Postumes et al. (1998), it is exactly because there are so few nonverbal cues to process in online environments that people more actively seek out norms of behavior in order to find acceptance among the other participants. A norm, as you might know, is an accepted social behavior. Using a fork to eat a salad is a norm, and people who comply with norms generally tend to find acceptance among others who practice the same. Let's say you enter a chat room in which you observe the other contributors using a lot of abbreviations in their messages, such as %%BTW%% for "by the way" and %%LOL%% for "laugh out loud." The SIDE model predicts that you are likely to pick up this norm for yourself. In doing so, you are likely to appear more attractive to those around you and thus have a better chance of initiating relationships
* Interestingly, the foundations of the SIDE model are built on psychological investigations into **mob mentality**. If you have seen news footage of a crowd in the midst of a riot, you may have questioned how people could ever behave so outrageously,smashing windows, setting fires, and looting stores. Clearly, these are all antisocial behaviors, yet they are committed in a very social moment. Psychologists call this process **deindividuation** because personal identity is decreased in favor of one's social identity. This social identity reacts to the situation and correspondingly takes its cues for appropriate behavior from others in the same situation. Thus, although looting a television set from a store window display might seem like an outrageous act to commit in the context of an everyday stroll down Main Street, in the midst of a riot,where others are making off with all kinds of home electronics, taking the TV appears to be the appropriate thing to do.
* Over the last decade, Postumes et al. have conducted a series of experiments with group interaction to establish the power of the SIDE model to predict human behavior.These studies have suggested two important qualities to this processes. First, **visual anonymity** among participants in a group seems to __foster stronger SIDE__ effects toward conformity and group norms than in groups where participants saw one another face to face. Second, anonymity also seems to __encourage stronger self-categorization__ among users. In one experiment where the participants were made aware of one another's gender, the communicators tended to behave along the lines of their gender roles more than those to whom this information was not disclosed.
* In summary, the SIDE model predicts that people will __set aside personal identity and adopt the appropriate social identity in order to find acceptance among others__. We can observe this same subversion of the personal self in favor of social self on a typical
playground.
* __The other side of the SIDE model__ is, of course, that of **the receivers**. Even as the individual must struggle to figure out the norms of a group, the group must struggle to figure out whether or not the individual has the qualities to be "one of the gang." This results in a reliance on stereotyping in order to define who this other is. One individual actively attributes a great deal of meaning to the evident behaviors of the other during their interactions. Quite often then, __one will turn to **stereotypes** to help decode this behavior.__ Stereotyping is one way in which we try to make sense of the world by focusing on what we might believe to be certain patterns of behavior exhibited by members of a group. Thus, if an individual introduces him- or herself as a hacker, your stereotype of hackers might lead you to conclude that the person is technically proficient with programming and prompt in you a favorable evaluation of the individual.
* **Perceived similarity** has long been held to be a strong predictor of individual attraction (Trenholm & Jensen, 2000), and it seems to be a key in explaining the SIDE model's effects in cyberspace. More recently, researchers have found support for the SIDE model in fostering resistance against certain outgroups. For instance, they found that students were more likely to find support among their peers and consequently express opinions deemed unacceptable by faculty when communicating through computer-mediated channels (Spears, Lea, Cornelliussen, Postumes, & Harr, 2002).
====== Readings ======
* 이은주. (2008). 탈개인화 효과에 관한 사회적 자아정체성 모델. __커뮤니케이션 이론, 4__(1), 7-31.
* Postmes, T., Spears, R., Lee, A. T., & Novak, R. J. (2005). Individuality and Social Influence in Groups: Inductive and Deductive Routes to Group Identity. __Journal of Personality and Social Psychology, 89__(5), 747-763. doi: 10.1037/0022-3514.89.5.747
====== Walther's interpersonal communication in CMC ======
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 is, as a unified perception based on of whether others online seem to belong to the same group that is salient to the user, rather than as a sum or average of one’s perceptions of each other partner in a conversation.
The model also specified, theoretically, that when a deindividuated CMC user orients to an individualistic identification rather than a social identification, then systematic effects on similarity and attraction should not occur. The model views interpersonal (rather than group) attraction toward other members as an aggregation of randomly distributed values based on a person’s attraction to each idiosyncratic individual. That is, when perceiving others individually, one may like one person a lot, dislike another person a lot, and like others to different degrees, which, on balance, should average to some neutral level.
Attraction to a group to which one belongs, in contrast, should be systematically positive. This difference in the form of attraction marks a key distinction between a group-based and an interpersonally based approach to the social dynamics of CMC (Lea, Spears, & de Groot, 2001; for a review, see Walther & Carr, 2010).
The most basic research strategy that provided evidence for SIDE involved experiments manipulating the two factors, visual anonymity and type of identification. In a prototypical experiment, one half of the small groups of CMC users in an experiment would communicate with one another using a text-based chat system only, whereas the other half would use the chat system and be shown photos that were supposed to represent the members. The former condition provides visual anonymity, presumably instigating deindividuation, whereas the latter condition involves visual identification and individuation.
The second factor, group identification, is manipulated by prompting participants explicitly to look for the unique and distinctive characteristics of the group in which they were involved rather than to try to detect what made the individuals with whom they were conversing unique and different from one another. Such research has produced predicted interaction effects of visual anonymity/identifiability by group/interpersonal identity, with conditions involving both visual anonymity and group identity providing the greatest scores on attraction (e.g., Lea & Spears, 1992).
The SIDE model’s advocates originally argued that the nature of group memberships with which CMC users identified comprised fairly general social categories (e.g., English vs. Dutch nationalities, psychology vs. business majors, men vs. women, etc.). Although attempts to arouse these kinds of identifications have been employed in SIDE experiments, they have not produced effects as clearly as when identification was targeted only with the local group, that is, the unique and specific small group involved in the interaction. These results have led to revisions of the SIDE model, and recent versions focus on visually anonymous CMC leading to in-group identification with the group of participants rather than via larger social categories.
Although the SIDE model is distinctively not about an interpersonal basis for online relations, it has been argued to offer an explanatory framework for what others consider to be interpersonal phenomena. Lea and Spears (1995) argued that SIDE can explain the development of romantic relationships online. Rejecting notions that intimate attraction is necessarily and exclusively premised on physical appearance or the exchange of nonverbal cues (a rejection with which several other CMC theories in this chapter, described below, concur), they argued that intimacy may result from the perceptions of similarity that arise from a couple’s shared membership in a variety of social categories (see also Sanders, 1997). From this perceptive, although partners who communicate romantically online may believe that they love each other interpersonally, this would be an illusion. Their projection of interpersonal intimacy would be an outgrowth and projection of the similarity/attraction they share on the basis of their social (rather than interpersonal) identifications. Other essays have made quite strident pronouncements about the superiority of a groups-based, rather than an interpersonally-based, approach to understanding 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.