Social impact theory

Social impact theory was created by Mariah Castonguay in 1981 and consists of four basic rules which consider how individuals can be "sources or targets of social influence".[1] Social impact is the result of social forces including the strength of the source of impact, the immediacy of the event, and the number of sources exerting the impact.[2] The more targets of impact that exist, the less impact each individual target has.[3]

Original research

Social impact theory is a theory that uses mathematical equations to predict the level of social impact created by specific social situations. The theory was developed in 1981 by Bibb Latané, a psychologist who was working at Ohio State. Latané described social impact as a phenomenon in which people affect one another in social situations. Through daily experiences such as embarrassment, persuasion, humor, and a plethora of other experiences, one can see the number of situations that are governed by the presence and actions of others. The impact can not only be observed visually, it also alters 'forces' within the target such as thoughts, attitudes, incentives and physiological state. Latané noticed that social impact was governed by three laws that can be translated into mathematical equations. These laws are social forces, psychosocial law and multiplication/division of impact.

Social forces

The first law claims that when social forces function within a social structure, the result is social impact. Latané explained this interaction as That is, social impact is affected by strength (S), immediacy (I) and number of people (N). This theory postulates that the greater the number of sources of social impact in a social situation, the greater the impact would be. Thus, the equation Impact = f(SIN) describes social impact as a multiplicative function based on the number of people acting on the target. Within this equation:

The I = f(SIN) equation illustrates that there is more social impact when higher status individuals are the source, when the action is more immediate, and when there are a greater number of sources.

Psychosocial law

The Psychosocial law states that the most significant difference in social impact will occur in the transition from 0 to 1 source and as the number of sources increases, this difference will become even eventually. The equation Latané uses for this law is That is, some power (t) of the number of people (N) multiplied by the scaling constant (s) determines social impact. Latané applied this theory to previous studies done on imitation and conformity as well as on embarrassment. Asch’s study of conformity in college students contradicts the psychosocial law, showing that one or two sources of social impact make little difference. However, Gerard, Wilhelmy, and Conolley conducted a similar study on conformity sampling from high school students. High school students were deemed less likely to be resistant to conformity than college students, and thus may be more generalizable, in this regard, than Asch’s study. Gerard, Wilhelmy, and Conolley’s study supported the psychosocial law, showing that the first few confederates had the greatest impact on conformity. Latané applied his law to imitation as well, using Milgram’s gawking experiment. In this experiment various numbers of confederates stood on a street corner in New York craning and gawking at the sky. The results showed that more confederates meant more gawkers, and the change became increasingly insignificant as more confederates were present. In a study Latané and Harkins conducted on stage fright and embarrassment, the results also followed the psychosocial law showing that more audience members meant greater anxiety and that the greatest difference existed between 0 and 1 audience members.

multiplication/divisions of impact

The third law of social impact states that the strength, immediacy, and number of targets play a role in social impact. That is, the more strength and immediacy and the greater number of targets in a social situation causes the social impact to be divided amongst all of the targets. The equation that represents this division is This law relates to diffusion of responsibility, in which individuals feel less accountable as the number of people present increases. In emergency situations, the impact of the emergency is reduced when more people are present.

The social impact theory is both a generalizable and a specific theory. It uses one set of equations, which are applicable to many social situations. For example, the psychosocial law can be used to predict instances of conformity, imitation and embarrassment. Yet, it is also specific because the predictions that it makes are specific and can be applied to and observed in the world. The theory is falsifiable as well. It makes predictions through the use of equations; however, the equations may not be able to accurately predict the outcome of social situations. Social impact theory is also useful. It can be used to understand which social situations result in the greatest impact and which situations present exceptions to the rules.

While Social Impact theory explores social situations and can help predict the outcomes of social situations, it also has some shortcomings and questions that are left unresolved. The rules guiding the theory depict people as recipients that passively accept social impact and do not take into account the social impact that people may actively seek out. The model is also static, and does not fully compensate for the dynamics involved in social interactions. The theory is relatively new and fails to address some pertinent issues. These issues include finding more accurate ways to measure social outcomes, understanding the “t” exponent in psychosocial law, taking susceptibility into account, understanding how short-term consequences can develop into chronic consequences, application to group interactions, understanding the model’s nature (descriptive vs. explanatory, generalization vs. theory).

Subsequent development

The Dynamic Social Impact Theory was developed by Latané and his colleagues in 1996. This theory is considered an extension of the Social Impact Theory as it uses its basic principles, mainly that social influence is determined by the strength, immediacy, and number of sources present, to describe how majority and minority group members influence one another. As its name suggests, the Dynamic Social Impact Theory proposes that groups are complex systems that are constantly changing and are never static. Groups that are spatially distributed and interact repeatedly organize and reorganize themselves in four basic patterns: consolidation, clustering, correlation, and continuing diversity. These patterns allow for group dynamics to operate and ideas to be diffused throughout the group.[4]

1. Consolidation – as individuals interact with each other, over time, their actions, attitudes, and opinions become uniform. In this manner, opinions held by the majority of the group spread to the minority, which then decreases in size.

2. Clustering – individuals tend to interact with clusters of group members with similar opinions. Clusters are common when group members communicate more frequently with members in close proximity, and less frequently with members who are more distant. Minority group members are often shielded from majority influence due to clustering. Therefore, subgroups can emerge which may possess similar ideas to one another, but hold different beliefs than the majority population.

3. Correlation – over time, individual group members` opinions on a variety of issues converge and correlate with each other; this is true even of issues that are not discussed by the group.

4. Continuing Diversity – a degree of diversity can exist within a group if minority group members cluster together or minority members who communicate with majority members resist majority influence. However, if the majority is large or minority members are physically isolated from one another, this diversity drops.

Contemporary research

In 1985 Mullen analyzed two of the factors that Latané associated with Social Impact theory. Mullen conducted a meta-analysis that examined the validity of the source strength and the source immediacy. The studies that were analyzed were sorted by the method of measurement used with the self-reported in one category and the behavior measurements in the other category. Mullen’s results showed that the source strength and immediacy were only supported in cases in which tension was self-reported, and not when behavior was measured. He thus concluded that Latané’s source strength and immediacy were weak and lacked consistency. Critics of Mullen’s study, however, argue that perhaps not enough studies were available or included, which may have skewed his results and given him an inaccurate conclusion.

A study conducted by Constantine Sedikides and Jeffrey M. Jackson took another look at the role of strength and within social impact theory. This study was conducted in a bird house at a zoo. In one scenario, an experimenter dressed as a bird keeper walked into the bird house and told visitors that leaning on the railing was prohibited. This was considered the high-strength scenario because of the authority that a zookeeper possesses within a zoo. The other scenario involved an experimenter dressed in ordinary clothes addressing the visitors with the same message. The results of the study showed that visitors responded better to the high-strength scenario, with fewer individuals leaning on the railing after the zookeeper had told them not to. The study also tested the effect that immediacy had on social impact. This was done by measuring the incidences of leaning on the rail both immediately after the message was delivered and at a later point in time. The results showed that immediacy played a role in determining social impact since there were fewer people leaning on the rails immediately after the message. The visitors in the bird house were studied as members of the group they came with to determine how number of targets would influence the targets’ behavior. The group size ranged from 1 to 6 and the results showed that those in larger groups were less likely to comply with the experimenter’s message than those in smaller groups. All of these findings support the parameters of Latané’s Social Impact Theory.

Kipling D. Williams, and Karen B. Williams theorized that social impact would vary depending on the underlying motive of compliance. When compliance is simply a mechanism to induce the formation of a positive impression, stronger sources should produce a greater social impact. When it is an internal motive that induces compliance, the strength of the source shouldn’t matter. Williams and Williams designed a study in which two persuasion methods were utilized, one that would evoke external motivation and one that would evoke internal motivation. Using these techniques, experimenters went from door to door using one of the techniques to attempt to collect money for a zoo. The foot-in-the-door technique was utilized to evoke the internal motive. In this technique, the experimenter would make an initial request that was relatively small, and gradually request larger and larger amounts. This is internally motivated because the target’s self-perception is altered to feel more helpful after the original contribution. The door-in-the-face technique, on the other hand, involves the experimenter asking for a large amount first; and when the target declines, they ask for a much smaller amount as a concession. This technique draws on external motivation because the request for a concession makes one feel obliged to comply. The experiment was conducted with low-strength and high-strength experimenters. Those who were approached by higher-strength experimenters were more likely to contribute money. Using the different persuasion approaches did not produce statistically significant results; however, it did support Williams and Williams hypothesis that the strength of the experimenter would heighten the effects of the door-in-the-face technique, but have minimal effect on the foot-in-the-door technique

There have also been studies done to examine Latané’s dynamic social impact theory. One study was conducted within three classrooms. Two of these classes were small and one of them was large. The experimenter would develop 10 moderate multiple choice questions, which were read aloud to the class one at a time. The students were then instructed to discuss each question as it was read aloud with their neighbors and come to a final answer at the end of the given time period. The results of this simple study were able to illustrate and support the effects of dynamic social impact theory. The answers were consolidated because many of those with a minority answer within their group would comply with the majority opinion, which reduced the diversity of the answers. There was also considerable clustering: those sitting near each other tended to have the same answers. Correlation was visible because answers that weren’t originally apparently related, became connected for students within some of the groups. However, none of the answers were entirely eliminated, allowing for continuing diversity. Many of the groups had members that changed their answers from the wrong answer to the right answer; however, there were also students that changed their answer to the wrong one after the discussion.

Most recently, Babajide Osatuyi and Katia Passerini [5] operationalized strength, immediacy, and number using Social Network Analysis centrality measures, i.e., betweeness, closeness, and degree centralities to test two of the rules stipulated in Social Impact Theory. They compared the influence of using Twitter and discussion board in a learning management system (e.g., Moodle and Blackboard) on student performance, measured as final grade in a course. The results provide support for the first law, i.e., impact (grade) as a multiplicative resultant of strength, immediacy, and number of interactions among students. Additional interesting insights were observed in this study that educators ought to consider to maximize the integration of new social technologies into pedagogy.

References

  1. ↑ Karau, Steven; Williams, Kipling (October 1995). "Social Loafing: Research Findings, Implications, and Future Directions". Current Directions in Psychological Science. 4 (5): 135. doi:10.1111/1467-8721.ep10772570. JSTOR 20182353.
  2. ↑ Michael A. Hogg, Scott Tindale; Blackwell Handbook of Social Psychology: Group Processes; John Wiley & Sons (2008); p.239; ISBN 047099844X,
  3. ↑ Karau, Steven; Williams, Kipling (October 1995). "Social Loafing: Research Findings, Implications, and Future Directions". Current Directions in Psychological Science. 4 (5): 135. doi:10.1111/1467-8721.ep10772570. JSTOR 20182353.
  4. ↑ Forsyth, D.R. (2009). Group dynamics: New York: Wadsworth. [Chapter 7]
  5. ↑ Osatuyi, B. and Passerini, K. (in press), Twittermania: Understanding how social media technologies impact engagement and academic performance of a new generation of learners, Communications of the AIS

Sources

Further reading

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