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Final Paper, Draft One

Infrahumanization in computer-mediated communication
Bryce T. Hoffman
Cornell University
334 Kennedy Hall
Ithaca, NY, 14850
bth25@cornell.edu

Ishan Chellaney
Cornell University
Ijc6@cornell.edu

Matthew Sutherland
Cornell University
mws36@cornell.edu
Jeffrey Hancock
Cornell University
jth34@cornell.edu

Matthew Manacher
Cornell University
mtm36@cornell.edu

Deborah Tan
Cornell University
dqt2@cornell.edu

ABSTRACT
This study examines whether computer-mediated communication (CMC) leads to greater evidence of infrahumanization than face-to-face communication. In line with the Social Identity Deindividuation Effect (SIDE), we find a stronger attribution of uniquely human emotions and human-associated words in face-to-face communication than in CMC. These findings are used to modify and extend current theoretical perspectives on infrahumanization within the context of intergroup relations.
Author Keywords
Infrahumanization, intergroup relations, cmc, computer-mediated communication, instant messaging, group dynamics
ACM Classification Keywords
H.5.3 [Information Interfaces and Presentation]: Group and Organization Interfaces—Computer-supported cooperative work, Organizational design; K.4.3 [Computers and Society]: Organizational Impacts—Computer-supported cooperative work, Reengineering, Automation
INTRODUCTION
It is well known that people on opposing sides of conflicts often have divergent ways of construing their social worlds. Groups serve the function of bringing like-minded individuals together but also set the stage for bias against outsiders, ranging from subtle derision to deadly violence. In a pluralistic society with innumerable groups and conflicts, it is valuable to identify factors that can foster intergroup understanding or at least minimize the detrimental effects of bias. The purpose of this study is to compare evidence of a particular form of bias, infrahumanization [1], when group members communicate via computer-mediated technology and when they communicate in a face-to-face setting. After a brief review of the relevant literature, we present the results of our study aimed at providing theoretical insight into our understanding of this subtle but potentially serious form of intergroup bias. In doing so, we will focus on how identity within a group may develop as a function of intergroup dynamics.
Infrahumanization
Infrahumanization refers to the tendency of group members to associate more uniquely human attributes to members of the ingroup than the outgroup. This has most often been studied through the attribution of emotions to ingroup and outgroup members. Leyens has argued that emotions can be categorized into two types: primary emotions that both human and animals can feel (such as anger, surprise, fear, and disgust) and secondary emotions, which are experienced only by humans. These include such complex emotions as admiration, fondness, disillusion, contempt, and conceit [2].
A key finding of infrahumanization research is that people tend to attribute secondary emotions more readily to ingroup members than to outgroup members [3]. Aside from emotion words, evidence suggests people tend to attribute more human-related words to the ingroup members and more animal-related words to the outgroup members [4]. While thought to occur on a subconscious level, studies have linked infrahumanization with behavioral effects. Denying the humanity of outgroup members can have negative effects on social interactions, such as nonintervention in cases of emergency [5].
Because communication is the point of intersection between all groups—and because of what is known about the factors that mediate infrahumanization—it seems especially valuable to study this phenomenon in a communication context. By comparing face-to-face communication to computer mediated communication, this study provides a unique scope to examine the effects of infrahumanization. The different settings and cues inherent in the face-to-face and CMC environments present an intriguing opportunity for further analysis.
The SIDE model
The SIDE model (Social Identity Deindividuation Effect) provides a useful platform for exploring infrahumanization in a communication context [6]. The SIDE model suggests that anonymity can enhance social influence when a group identity is made salient. Social identity is salient when group members are identified as members of a group rather than as individuals. When social identity is salient, and members are made visually anonymous, group identification effects such as stereotyping and compliance with normative behavior are enhanced [7]. In addition to exaggerated group identification effects, the SIDE model suggests that visual anonymous groups are more conducive to social influence than visually identifiable groups. In other words, visual anonymity increases group salience, which consequently increases social influence [8].
Hypotheses
Thus, when comparing face-to-face with computer-mediated forms of communication, SIDE suggests that the visual anonymity of CMC will lead to overattributions and exaggerated group identification effects. From an infrahumanization perspective, we can expect to see similar effects. When group identity is made salient, and members are visually anonymous, we should expect to see exaggerated effects of infrahumanization. From the established SIDE and infrahumanization literature, we hypothesize the following:
H1: A greater degree of infrahumanization when describing the outgroup than the ingroup (for both FtF and CMC)
We predict that across all conditions we would find the classic infrahumanization effect of people attributing human characters preferentially to the ingroup.
H2: A lesser degree of infrahumanization when describing the individual partner than the group (for both FtF and CMC).
We predict that across all conditions we would find that identifying the outgroup member as an individual rather than the group member would mitigate the infrahumanizaiton effect.
H3a: A greater degree of infrahumanization in CMC than FtF when describing outgroup members
H3b: A lesser degree of infrahumanization in CMC than FtF when describing ingroup members
We predict that visual anonymity will exaggerate the effects of infrahumanization. We expect a greater degree of infrahumanization when describing the outgroup and lesser degree of infrahumanization when describing the ingroup in both CMC and FtF, but to a greater degree (in both directions) in CMC.
METHOD
Participants were recruited for a research study on “political negotiation” and told that they would have a conversation with someone whose views may or may not be different from their own before answering a few simple questions.
Upon signing an informed consent form and filling out a short survey about their political attitudes, political party membership, and strength of identification, participants were brought to a designated location in order to participate in either a face-to-face discussion or a computer-mediated discussion. Separate testing rooms for the instant messaging conversation were set up with a desk and computer with an instant messaging program. For the instant messaging conversation, subjects were prevented from seeing each other prior to their participation so as to preserve visual anonymity. For the face-to-face conversation the test subjects were brought together in one room where they participated in the study.
Participants were asked to come to agreement on what they believed to be a fair letter grade for the Obama administration. They were given a ten-minute time limit.
Group membership was made salient by informing each participant of their own and their partner’s political views prior to the exercise. Subsequent to the ten-minute discussion, all participants were separated and asked to complete a word selection task.
Based on pilot testing, we created a list of 32 descriptive terms in four categories: primary and secondary emotions, human-animal descriptors, morality judgments, and warmth-competence terms. Each category contained eight words and was balanced for valence. The emotion and human-animal categories were also balanced with four uniquely human words and four non-uniquely human words. All words were presented in a randomized order.
Participants were asked to choose eight words from the list they felt best described their partner. Using the same set of words, participants were then asked to choose sixteen words—the eight they felt best described members of their ingroup in general and the eight they felt best described members of the outgroup in general. For this second portion of the task, all 32 words were available but participants were asked not to ascribe the same word to more than one group, thus if a participant described Democrats as “folksy” s/he could not also describe Republicans with that term.
RESULTS
Data were obtained from 16 participants, 10 males and six females. Thirteen participants self-identified as Democrats, three as Republicans. This allowed for three intergroup pairings of Republicans with Democrats and five intragroup pairings, all Democrats. One set of responses was discarded because a participant did not follow the directions provided. Fifteen response sets are included in this analysis.
Based on pilot testing, eight of the 32 possible descriptors respondents could choose in their word selection task were identified as “uniquely human.” Four represented secondary emotions: hopeful, resentful, disenchanted, and optimistic. Four were characteristics that can describe humans but not animals: educated, citizen, folksy, and criminal.
For each participant, three scores were calculated based on the number of “uniquely human” attributes they ascribed to 1) their partner 2) outgroup members in general and 3) ingroup members in general. These scores were then averaged across all participants and according to each of the experimental conditions. The differences reported in this section, then, are differences in the average number of uniquely human words used to describe the relevant target individual or group.
Because of the small sample size, results will neither be analyzed nor discussed in terms of statistical significance. However, trends in the data relative to our hypotheses can be identified.
Our first hypothesis predicted the classic infrahumanization effect. We expected that participants across all conditions would preferentially attribute uniquely human qualities to the ingroup over the outgroup. Our second hypothesis predicted that there would be less evidence of infrahumanization of partners (i.e. the person they talked to) than of generic group members (i.e. Republicans or Democrats in general).
Our data appear to offer support for both hypotheses. Overall, participants described their partners with the greatest number of uniquely human words, using an average of 3.27 (SD=.8). Ingroup members in general were described with slightly fewer at 3 (SD=1.1). As predicted, there was a sharp decrease in the number of uniquely human words used to describe outgroup members in general, with an average of 1.73 (SD=1.1).
Our additional hypotheses predicted:
• H3a: That infrahumanization of the outgroup would be exaggerated among participants in the CMC condition. (see Figure 1).

Figure 1. Comparison of the number of uniquely human words used to describe target groups after computer chat or face-to-face discussion.
• H3b: That infrahumanization of the ingroup would be exaggerated among participants in the face-to-face condition.
Ingroups and outgroups alike were described with fewer uniquely human words by participants in the CMC condition, providing preliminary support for the former hypothesis but not the latter. As predicted, there was a sharp contrast in evaluations of the outgroup. Participants in the face-to-face condition used an average of 2.29 (SD=1.1) uniquely human words to describe the outgroup, while participants who spoke via instant messaging chose only 1.25 (SD=.9). Ingroup evaluations followed a similar but less dramatic pattern. Participants in the face-to-face condition chose 3.14 (SD=1.22) uniquely human words on average, while those in the CMC condition chose 2.87 (SD=.99).
CONCLUSION
Infrahumanization has far-reaching implications for the way we interact as a society. Whether or not we are becoming a more tolerant society that embraces different viewpoints or one that is increasingly polarized depends largely on the biases we display when communicating. With the ubiquity of CMC and the increasing globalization of this form of communication, the way we develop biases about “us” and “them” will significantly impact how we perceive, discriminate, and ultimately treat members of opposing groups.
Evidence from this study supports our hypothesis that the communication medium plays a significant role in infrahumanization. While CMC may foster bias and reinforce preconceived notions in intergroup dialogue, one solution may be to individuate people within CMC spaces. The effects of CMC on infrahumanization have demonstrated some consistency with SIDE and further integration of these theories should be explored.
ACKNOWLEDGMENTS
We thank our participants, Ashley Downs for her logistical support, and all who have assisted in the development of this research.
REFERENCES
1. Leyens, J-P., Demoulin, S., Vaes, J., Gaunt, R., Paladino, M. (2007). Infra-humanization: The wall of group differences. Social Issues and Policy Review, 1, 139-172.
2. Demoulin, S., Leyens, J.-P., Paladino, M., Rodriguez-Torres, R., Rodriguez-Perez, A., & Dovidio, J., (2004). Dimensions of ‘uniquely’ and ‘non-uniquely’ human emotions. Cognition and Emotion, 18(1), 71-96
3. Leyens,J-P., Paladino, P., Rodriguez-Torres, R., Vaes, J., Demoulin, S., Rodriguez-Perez, A., et al. (2000). The emotional side of prejudice: The attribution of secondary emotions to ingroups and outgroups. Personality & Social Psychology Review (Lawrence Erlbaum Associates), 4(2), 186-197. Retrieved from Academic Search Premier database.
4. Viki, G., Winchester, L., Titshall, L., Chisango, T., Pina, A., & Russell, R. (2006). Beyond secondary emotions: the infrahumanization of outgroups using human-related and animal-related words. Social Cognition,24(6), 753-775. Retrieved from Academic Search Premier database.
5. Vaes, J., Castelli, L., Paladino, M., Leyens, J-P., Giovanazzi, A. (2003). On the Behavioral Consequences of Infrahumanization: The Implicit Role of Uniquely Human Emotions in Intergroup Relations. Journal of Personality and Social Psychology, 85(6), 1016-1034.
6. Postmes, T., & Spears, R. (1998). Deindividuation and anti-normative behavior: A meta-analysis. Psychological Bulletin, 123, 238-259.
7. Reicher, S. D., Spears, R., & Postmes, T. (1995). A social identity model of deindividuation phenomena. In W. Stroebe & M. Hewstone (Eds.), European review of social psychology, Vol. 6 (pp. 161-198). Chichester, UK: Wiley.
8. Postmes, T., Spears, R., Sakhel, K., & de Groot, D. (2001). Social Influence in Computer-Mediated Communication: The Effects of Anonymity on Group Behavior. Personality and Social Psychology Bulletin, 27, 1242-1254.
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Presentation

The INGroup’s presentation on ‘The Role of Infrahumanization in Communication’:

Please find some notes outlining Walther & Parks (2002) study entitled “Cues Filtered In, Cues Filtered Out.”

Main Idea: Nothing is empirically tested in this study.  Rather, the authors provide a review of several prominent computer mediated communication (CMC) theories.

Important Theories:

Cues Filtered Out – The greater the bandwidth (number of communication cues) a system affords, the greater the social presence of communicators.  Walther & Parks discredit this theory due to time restrictions.  Also, group identity and attitude are not taken into consideration.

Media Richness Theory – the more emotionally charged the subject matter, the more complex media is required.  Therefore, texting is not an adequate forum for emotional issues (533).

Social Information Processing (SIP) – Communicators exchange social information through the content, style and timing of verbal messages on-line.  This diverges from traditional CMC thinking, which suggests that the lack of nonverbal cues restricts the flow of social information (535).

Mixed-Mode Relationships – people meet on-line and migrate off-line (550).

SIDE (539) – This theory seems to draw the least amount of criticism from Walther & Parks although they do note its shortcomings in terms of its application to interpersonal relationships.

I’ve provided below an overview of Vaes and Paladino’s paper on “The uniquely human content of stereotypes”. Let me know if you have questions.

Vaes and Paladino’s paper underlying aim is to discern the linkages between infrahumanization and intergroup stereotyping and extend this to the affinity between uniquely human and competence factors. In essence, the question is whether stereotypes associated to a group entail a uniquely human dimension.

The paper discusses the following:

In-group stereotypes – more human as opposed to out-group stereotypes, which are formulated as a consequence of the denial of out-group humanity. This occurs when the out-groups lack warmth and competence.

Stereotype Content Model (SCM) – This model illustrates how the relative status of a group plays a crucial role in ascribing the level of “perceived warmth” through

i) degree of competence, and

ii) type of interdependence (if competitive or not)

From this, four inter-group stereotypes emerge:

1) Competent and warm (i.e. in-group)

2) Competent but not warm (High status/competitive groups),

3) Incompetent but warm (Low status/uncompetitive groups)

4) Neither competent nor warm (Low status, competitive groups).

It is within this context that the paper aims to demonstrate which of the groups derived from SCM are more susceptible to being infrahumanized.

One thing to not is that when the out-group is infrahumanized, “both positive and negative secondary emotions are denied”. 3 hypotheses derived from earlier research are tested:

1) Infrahumanization hypothesis – this target-based approach to infrahumanization theory claims that the infrahumanization bias should occur in all “inter-group comparisons independently of the out-group’s position according to the SCM”.

2) Low–low out-group hypothesis – Based on the findings of Harris and Fiske (2006), low–low out-groups are infrahumanized to a larger degree than other out-groups as they are denied “full humanness”.

3) Competence hypothesis – The third and most important hypothesis examines the connection between stereotype content and the varied forms of humanness. It predicts that high competence/low warmth outgroups will be perceived as most uniquely human.

Conclusions:

By exploring the human content of stereotypes, the paper’s findings show that the in-group is always identified as uniquely human, even when seen differently in terms of competence and warmth (based on the SCM). In this regard, Vaes and Paladino extend the infrahumanization bias to intergroup stereotypes.

Cues filtered out perspectives


Social Presence Theory

  • Greater bandwidth allows for more cues
  • Nonverbal cues make communicators more salient to each other
  • Thus, the greater the bandwidth, the greater the social presence
  • CMC results in less impression formation

Reduced Social Context Cues

  • Focused on lack of nonverbal cues to express purpose, decorum, status and affect
  • Leads to focus on task and self, and hostile, disinhibited behavior
  • When you don’t have all the cues, people behave in more selfish ways (focus more on self)
  • CMC will lead to poorly developed ,negative impressions of people

Hancock and Dunham: Results

  • CMC Breadth < FTF Breadth (in support of Social Presence Theory)
  • CMC Intensity > FTF Intensity (somewhat against Reduced Social Context Theory.  Impressions were more intense but not necessarily more negative)

In our study we want to examine the Social Identity Model of Deindividuation Effects (SIDE). The SIDE theory was developed and first named in 1991 by Lea and Spears, and then later expanded on in 1992. This theory is important in understanding computer mediated technology and communication.  The SIDE model expands on the basic deindividuation theory that examines how in crowds people will act in ways that are often not perceived as rational. When somebody is in a crowd there is a certain amount of anonymity that can effect how they will act. For example, normally if a rational person did not agree with a controversial decision made by a company, they would not usually go up to the company’s building by themselves and throw a glass bottle at it. On the other hand if a person is in a crowd of one hundred people and everyone is throwing glass bottles, then the person may be inclined to act irrational and proceed to deface the building with glass bottles.

The SIDE model even more examines anonymity and how anonymity changes the salience of personal identity and social identity, thus having a profound effect on behavior. In our study we are asking people to choose a side on a subject in which they have strong feelings about as well as a concrete opinion, and then discuss these views with someone that has the opposite opinion. To keep the study valid, it is important that people are kept anonymous in order to have the full effect. We were thinking about just giving people standard instant messaging user names, so that for example user 1 would be having a conversation with user 2, and both users will have conflicting views on the subject matter.

The cognitive side of the SIDE model deals with group immersion and anonymity and the salience with personal and social identities. Anonymity in a group can enhance the salience of social identity and depersonalize the social perceptions of others and the self. This can also lead to people perceiving others in terms of stereotypes.

In some situations, making an individual identifiable can promote a stronger social categorization. SIDE describes the cognitive processes by which the salience of social identity is affected by making information individuated or by eliminating individuated information. On the strategic side of the use of SIDE, anonymity can have strategic consequences, and can affect the ability for people to express their personal and social identities. Strategic concerns come into play when an out-group has more power than the in-group, or when the norms of both groups are different. When this happens, the identifiably of the in-group towards the out-group will shift the power between groups. The identifiably towards a more powerful out-group will limit the degree to which the in-group’s identity can be expressed freely.

SIDE is used in order to explain the effects of anonymity and social isolation in various contexts. SIDE can be used to do research with online teams and electronic relationships.

Coding – Euphemistic Discourse

Email Coding

Euphemism Definition:

According to McGlone & Batchelor, the underlying definition of euphemism is “an expression referring to a stimulus that is perceived as more polite than the stimulus’ conventional literal label.” It is this linguistic substitution of a more agreeable expression in place of the original expression itself that this study examines. Such euphemistic circumlocutions are discerned through the coding of emails.

Coding Scheme:

1. Omit salutations and sign-offs, such as ‘sincerely’ and ‘regards’.
2. Separate out the ideas contained in each email: Disparate ideas are segmented into individual sentences.
3. Code each idea unit ( 1 = if it contains 1 or more euphemisms; 0 = no euphemism)

Results:

Inter-coder reliability: 89.8%
Percentage of euphemisms found (and agreed on): 0.88%

Confusion matrix:

Percentage of errors occurring because coder 1 coded euphemism and coder 2 did not: 100%
Vice versa percentage: 0%

Examples:

Two euphemisms we agreed on:
i) “I want to eat you for breakfast, lunch, evening tea, supper, and midnight snack.”
ii) ” I want to devour you.”

Status Analysis

When you email a professor, do you call her “Mrs.”?  “Ms.”?  “Professor”?  What if she earned her doctorate degree?  This only complicates things further.  Alternatively, what if you are replying to your brother’s third email in the span of an hour?  Does your attitude change?  Do you even address him directly or does sharing the same family tree preclude him from a proper introduction?  The underlying presumption is that one’s tone, words and context of what is written changes depending upon the status of the person receiving the email.  Through a meticulous analysis of 25 emails sent to “low status” individuals and 25 emails sent to “high status” individuals, we discovered some intriguing differences in the parts of speech and semantic value in each corpus.

By examining the parts of speech applied in high and low status emails, our group focused exclusively on the individual words that were used without applying context to what was written.  One trend we discovered was that we used the preposition “of” more often in high status emails compared to low status emails. The reason for this could be when writing emails to high status emails, we may want to be very descriptive and carefully explain things; whereas, when we wrote emails to low status people, we were not as concerned with coming across crystal clear. On a similar note, words like “being” were used more in high status emails in order to be descriptive. Also, the preceding noun of a title was more evident in high status emails, which undoubtedly have an inherent formal and professional tone compared to low status emails

In terms of semantic analysis, the time period category manifested itself the most in both high and low status emails.  Although the frequency of time in high status emails edged out the frequency of time in low status emails 37-26, it is understandable that time plays a pivotal role in both high and low status emails.  These emails referred specifically to work and school deadlines or specific dates.  Time appears to be the only category for which the status of the email does not impact the frequency.  Education was one of the main areas of focus in high status emails compared to low status emails.  For example, every undergraduate in the group included at least one email to a professor as a high status email.  Money also served as a main discussion point in high status emails.  One may attribute this to the fact that our group is largely comprised of students, who are conversing with prospective employers and/or discussing funds devoted to a particular on campus group or association.  The topic of money may also seem prevalent since one of the group’s members owns his own business.

Although several differences were also demonstrated in other categories, the frequencies of time, education and money were the most prevalent.  Similarly, in the parts of speech analysis, prepositions and official titles accounted for the most prevalent occurrence.  While our suspicions that official titles, such as “Mr.” and “Dr.”, were applied more frequently in high status emails, this analysis also generated some unexpected results.  The fact that time, education and money frequently occurred in high status emails may not have been as easy to surmise prior to the analysis.  However, after a thorough examination of our group’s emails, it seems obvious that these categories would account for the largest frequencies.

Research Proposal

The InGroup Research Proposal


It is well known that people on opposing sides of conflicts often have  divergent ways of construing their social worlds. Where an insurgent sees a martyr, a Western soldier may see a terrorist. Where an environmentalist sees devastation, a mineworker may see economic opportunity. Groups serve the function of bringing like-minded individuals together but also set the stage for bias against outsiders, ranging from subtle derision to deadly violence. In a pluralistic society with innumerable groups and conflicts, it is valuable to identify factors that can foster intergroup understanding or at least minimize the destructive effects of bias.

Against this backdrop, we propose a study that will examine the  influence of different communication settings on a particular form of bias, infrahumanization (Leyens et al., 2000). Specifically, we wish to examine whether computer-mediated communication between members of opposing groups leads to greater evidence of infrahumanization than face-to-face communication. This investigation can provide theoretical insight into our understanding of this subtle-but-serious form of intergroup bias. It will also help to determine the usefulness of CMC as a tool for fruitful intergroup interaction.

Infrahumanization and Communication

Infrahumanization refers to the tendency of group members to reserve the full essence of humanity for members of their ingroup but not the outgroup (Leyens et al., 2007). This is most often studied by using the attribution of emotions to ingroup and outgroup members. Leyens has argued that emotions can be categorized into two types: primary emotions that both human and animals can feel (such as anger, surprise, fear, and disgust) and secondary emotions, which are thought to be experienced only by humans. These include such complex emotions as admiration, fondness, disillusion, contempt, and conceit (Demoulin et al., 2004). A key finding of infrahumanization research is that people tend to attribute secondary emotions more readily to ingroup members than to outgroup members (Leyens et al., 2000). The valence (positivity or negativity) of the emotions, regardless of primary or secondary, had no bearing (Leyens et al., 2000).

Interestingly, Leyens found that the infrahumanization effect was significantly diminished when outgroup members were established as individuals, for example by giving them names (Leyens et al 2001). This suggests that infrahumanization is more likely to occur in a low-context environment where group-level attributes take precedence over nuanced, personal interaction.  Additionally, the degree of infrahumanization relied on the relevance of the outgroup to the ingroup (Cortes et al., 2005).  If members of the outgroup were not perceived as somehow relevant to the fate of the ingroup, the degree of infrahumanization was reduced (Cortes et al., 2005).

While thought to take place on a subconscious level (Gaunt, Leyens & Demoulin, 2002), studies have linked infrahumanization with behavioral effects.  Denying the humanity of outgroup members can have negative effects on social interactions, such as nonintervention in cases of emergency (Leyens et al 2001). Vaes et al. (2003) demonstrated that when secondary emotions were evoked , people tended to approach ingroup members and avoid outgroup members.  The result was discrimination of outgroup members on the basis of expression (or lack thereof) of secondary emotions. In other words, the bias operating below our conscious awareness may still affect our conscious actions toward others.

Because communication is the point of intersection between all groups – and because of what is known about the factors that mediate infrahumanization – it seems especially valuable to study this phenomenon in a communication context.  Specifically, if individualization of outgroup members diminishes infrahumanization, then communications media that are rich in contextual information should provoke less bias in intergroup interactions than context-poor media. To date, such a link has not been studied by infrahumanization researchers despite its appeal as a means of fostering intergroup harmony or, at the least, avoiding unnecessary dischord.

Face-to-face communication and computer mediated communication are different. Whittaker (2003) explains the differences as a function of the “affordances” of various technologies.  For instance,  instant messaging may constrain an individual’s ability to communicate feedback compared to face-to-face communication, even though they share the qualities of being synchronous and bidirectional. Modes that different technologies support are considered one type of affordance (3).  Instant messaging provides only a linguistic mode while face to face communication includes an additional visual mode as well.  Interactivity, another affordance, measures the technology’s feedback speed (4).

Whittaker suggests without some type of feedback a “shared understanding and establishing common ground” is virtually impossible (35).  Unlike most theories of face-to-face interaction that do not attempt to explain the impact of visible behaviors on communication, Whittaker confirmed that factors such as “gaze and gesture” are integral to communicating interpersonal information (36).  As a result, technologies that do not transmit visual information concerning facial expressions “lead to interactions that are more impersonal and likely to end in deadlock” (35).  The underlying assumption is as the number of visual cues increase, so does the quality of the conversation on a personal and deeper level. This perspective dovetails nicely with the notion in infrahumanization research that the amount of interpersonal context may affect the level of bias generated during intergroup interactions. From this theoretical background, we derive the following hypothesis:

H1: Infrahumanization will be more pronounced when group members communicate via computer-mediated technology than when they communicate in a face-to-face setting.

Methods

The proposed study will examine the direct interactions of dyads, using mixed pairs composed of members of opposing groups.  Because of the established positive correlation between ingroup-outgroup relevance and strength of identification on infrahumanization, we propose to maximize those factors in our design so as to diminish the possiblity of mitigating infrahumanization through a confounding factor.

First, we will identify two topics of current relevance within our available sample pool, students at a large northeastern university. Participants will be asked to indicate their personal level of interest in those topics and also to indicate the strength and valence of their opinions. This measurement will be the basis of identifying individuals who are high-identifying members of opposing groups. At the time of the experiment, participants will be told they are part of a study on negotiation and that they will have a specified period of time to reach a creative solution concerning their area of disagreement. Each participant will be informed of the other participant’s group membership prior to the beginning of the conversation.

Conversations will take place either face-to-face or using an instant messaging program. Face-to-face conversations will be digitally recorded, and IM conversations will be logged as text.  While the participants in the instant messaging condition will not be permitted to see one another, they will be permitted the use of “emoticons” as a means of expressing emotion. No other nontextual information will be available to participants in the IM condition, but they will otherwise be free to express any information they feel is helpful and relevant. Individuals in the face-to-face condition will be permitted to speak freely, to touch, and to exchange any information they feel is relevant to their task.

When their time has expired, participants will be asked to turn in their solution (if they have one) and will then be given a paper-and-pencil evaluation form. It will ask them to list all of the emotions they felt and expressed during the conversation and all of the emotions their partner felt and expressed. A second measure will contain a matrix of animal-related words, neutral words, and uniquely human words. Participants will be asked to circle all of the words they felt applied to the communication style of their partner. Together, these two measures will evaluate the level of infrahumanization present in the interaction. Finally, participants will be asked to assess, on a seven-point scale, how typical they felt their partner was of their group. This measure will evaluate how individualized the outgroup member became during the course of the interaction, with the expectation that individualization would reduce typicality. While this study does not propose doing so, analysis of the voice and text data and of the solutions generated by the dyads may also prove fruitful.

Conclusion

Infrahumanization has far-reaching implications in the way we interact as a society.  Whether or not we are moving more towards a society that embraces different viewpoints or one that is increasingly polarized depends largely on the biases we display when communicating. With the ubiquity of computer-mediated communication and the increasing globalization of this communication, the way we form biases about “us” and “them” will significantly impact how we perceive, discriminate, and ultimately treat members of opposing groups.

References

Cortes, B., Demoulin, S., Rodriguez, R., Rodriguez, A., Leyens, J-P. (2005). Infrahumanization or Familiarity? Attribution of Uniquely Human Emotions to the Self, the Ingroup, and the Outgroup. Society for Personality and Social Psychology, 13(2), 243-252.

Demoulin, S., Leyens, J.-P., Paladino, M., Rodriguez-Torres, R., Rodriguez-Perez, A., & Dovidio, J., (2004). Dimensions of ‘uniquely’ and ‘non-uniquely’ human emotions. Cognition and Emotion, 18(1), 71-96

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Ideas White Paper *Draft-in-Progress*

 

The Ingroup is interested in exploring the effects of different conversational environments on subconscious forms of intergroup bias.  Specifically, we would like to study whether markers of bias are more pronounced when members of different groups engage in face-to-face conversation or when they interact in a computer-mediated setting.

Our prediction is that participants in face-to-face conversation will show less evidence of bias for several reasons. First, face-to-face conversation requires both parties to attend to more facets of maintaining the “face” of themselves and their partner, and this work will attune them to perceive the other person as an individual, not necessarily as just an example of a group. Also, face-to-face interaction provides a great deal more contextualizing information (facial expressions, body language, and so forth) that can assist in creating a personal connection that transcends simple social categorization. However, we acknowledge that the amount of contextual information available in computer-mediated forms of communication varies widely.

To study this question, we intend to identify polarizing issues of importance to Cornell students and then recruit students who feel strongly about those topics to participate in an experiment.  In the experiment, the participants will be given a limited period of time to interact with a person who belongs to an opposing group, and they will be asked to identify a creative way that they could compromise on the issue at hand. Afterward, participants will be asked to fill out a survey where they will rate their own communication and the communication of the other party.

We intend to measure two types of markers of intergroup bias, both of which have been established in the social scientific literature, infra-humanization and linguistic bias. Infra-humanization is a subtle form of bias where ingroup members subconsciously perceive the outgroup as less than fully human. To measure this, we will ask each participant to write down the emotions they felt and that they expressed in the conversation, and also to write down the emotions they felt the other person experienced and expressed. If ingroup members list a greater number of complex secondary emotions, such as guilt or indignation, for themselves and more animalistic primary emotions, such as anger, for the outgroup, it would be an indication of active infra-humanization. Another option would be to ask participants how typical they felt their conversation partner was of the outgroup as a whole.

Second, we will record the conversations of our participants using digital devices for face-to-face and chat logs for CMC in order to search for evidence of linguistic bias based on Semin and Fiedler’s Linguistic Category Model.  Under this model, we would expect references to the outgroup to follow a specific pattern where more abstract terms are used to describe negative qualities (e.g., Pro-choicers are evil) and concrete terms to describe positive qualities (e.g., that pro-choicer picked up that woman who fell down). The opposite would hold for the ingroup (i.e. Pro-lifers are righteous/that pro-lifer kicked the woman who fell down).

There are numerous questions we will need to settle to go forward with this study. What type of computer-mediated communication is best suited to this type of study? What ingroup-outgroup divisions will be most salient to the  people in our likely participant pool?  What resources will we need to carry off the study? Should we use more than one type of CMC? How can we be sure that any difference between CMC and face-to-face conversation isn’t merely the result of an anonymity effect?  If it is the result of an anonymity effect, is that a problem for our theory or a component of it? Finally, from a communication point of view, what theory are we going to ground our predictions in?