The founding paper for social impact theory was published by social psychologist Bibb Latané in 1981. The paper, titled “The psychology of social impact”, set forth three principles comprising a general theory/framework, leading to specific quantifiable and verifiable predictions. The principles are the social forces rule, the psychosocial rule and the multiplication versus division of impact principle.
Social impact, in Latane’s view, is caused by social dynamics such as the strength of the source of impact, the timing of the event, and the number of sources exerting the impact. The greater the number of impact targets, the less impact each one has.
Latane defines social impact as changes in physiological states and subjective feelings, motives and emotions, cognitions and beliefs, values and behavior, that occur
in an individual as a result of the real, implied, or imagined presence or actions of other individuals.
The social impact theory is both general and specific. It makes use of a single set of equations that apply to a wide range of social circumstances.
For example, the psychosocial principle can be used to forecast cases of compliance, imitation, and shame. However, it is also specific because the predictions it provides are specific and can be implemented and observed in the real world.
The theory is also falsifiable. It produces predictions using mathematics, although the calculations may not be accurate in predicting the result of social interactions.
Social Forces
The soical forces rule rests on three variables – strength, immediacy, and number. These factors interact in a formula, i = f(S * I * N). Small i here is social impact, S is strength of a specific source such as the age, socioeconomic status, previous relationship or potential forthcoming power over the target.
Capital I in the formula is immediacy, or how close in time or space the source is, or whether there are any meaningful barriers or filters or not. N means the number of sources existing. f can be some constant.
The idea here is likened by Latane to the impact of light falling on an object from one or more sources, for example, a light bulb. The analogous relationship exists between the quantity of light falling on a surface and the wattage or intensity of the light bulbs shining on it, as well as their proximity to the surface and number of bulbs.
Psychosocial Law
In behavioral economics, the first dollar has a higher subjective influence than the hundredth dollar. Not that you don’t desire 100 bucks instead of one, but the differential between 99 and 100 is smaller than the difference between 0 and 1.
Likewise, the difference in social impact on some social force coming from between zero and one people would be less than the difference between 99 and 100 people, according to the psychosocial law. The equation Latané uses for this law is Impact = sN’ (some power (t) of the number of people (N) multiplied by the scaling constant (s) determines social impact).
Contrary to what is suggested here by this law, some of the earliest and most well-known studies involving parametric variations in the number of individuals contributing to social impact seem to indicate a relationship quite different. In Asch’s study of conformity in college students, as the size of a group grows beyond three people, conformity does not appear to increase.
However, in contrast to Latane’s theory, which predicts that the first person added to a social setting will have the greatest influence, people who were surrounded by just one or two incorrect conformers in Asch’s experiment conformed very little.
Gerard, Wilhelmy, and Conolley carried out a similar study on conformity sampling among high school students. High school students were shown to be less likely to be resistive to conformity than college students, suggesting that their findings may be more generalizable than Asch’s. Gerard, Wilhelmy, and Conolley’s research corroborated the psychological law by demonstrating that the first few confederates had the largest influence on conformity.
Latané extended his law to imitation as well, utilizing Stanley Milgram’s gawking experiment. In this experiment, groups of confederates, ranging in size from 1 to 15, stood on a street corner in New York, craning and staring up at a building window on the sixth floor, behind which, barely discernible, was Milgram taking movies.
More confederates craning and staring at passersby resulted in more people craning and staring at passersby, but the amount of extra craning and staring caused by each additional craner and gawker decreased as the number of confederates increased.
In a study on stage fright and embarrassment, Latané and Harkins’ findings also supported the psychosocial law, indicating that the biggest difference was between 0 and 1 audience members and that larger audiences correlated with higher levels of anxiety. In an individual test conducted in a soundproof booth, sixteen college students were instructed to imagine that they were to recite a poem from memory in front of an audience.
They could control the level of a translucent screen’s brightness or a tone’s loudness by pushing buttons, adapting it to their expected social anxiety about performing in front of different-sized and status audiences. There were 1, 2, 4, 8, or 16 faces on the screen representing audiences who were either all male or all female, in their early teens or late thirties.
Participants increased the brightness and loudness of tone in response to the size of the audience. Audiences in their late thirties generated greater anxiety than audiences in their early teens, while male audiences produced more tension than female audiences.
Multiplication vs Division of Impact
In the third principle, the number, strength, and immediacy of targets affect the social impact. According to Latane, increasing the strength, immediacy, or number of other targets should result in a division or reduction of impact, with each person feeling less than he or she would if alone.
This reduction of impact is represented by the equation I = f(I/SIN). The effect of a social force from outside the group is divided by some root of the number of target people prenest, rather than the actual number of people.
This law is related to the diffusion of responsibility effect, in which individuals feel less accountable as the number of persons present grows. When more individuals are present during an emergency, the severity of the crisis is lowered.
Limitations
While social impact theory investigates social circumstances and can help anticipate their results, it has certain limitations and unanswered concerns. The theory’s norms depict people as passive recipients of social influence, ignoring the social impact that people may actively seek.
The model is also static, and it does not completely account for the dynamism of social relationships. The hypothesis is relatively recent and fails to address certain key difficulties.
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, applying to group interactions, and understanding the nature of the model (descriptive vs. explanatory, generalization vs. theory).
Although the theory describes the effects of social characteristics like as strength, immediacy, and number of sources, it does not explain how these influencing processes work. Experimenters fail to consider a number of aspects while putting the theory into practice.
Concepts like peripheral persuasion influence how communicators appear credible to some and untrustworthy to others. The characteristics differ from person to person, presumably linking strength with source credibility and beauty or immediacy with physical proximity.
As a result, in the application of the social impact theory, the concepts of persuasiveness, the ability to persuade someone with an opposing viewpoint to change, and supportiveness, the ability to assist those who agree with someone’s point of view in resisting the influence of others, are presented.
Finally, an individual’s likelihood of changing and being influenced is a direct function of strength (persuasiveness), immediacy, and the number of advocates, and it is inversely proportional to strength (supportiveness), immediacy, and the number of target individuals.
Dynamic Social Impact Theory
In later work, Latane and colleagues proposed the dynamic social impact theory, which, describes the influence of members between majority and minority groups. The theory is an extension of the original social impact theory (in which influence is determined by the strength, immediacy, and quantity of sources present) and explains how groups, as complex systems, adapt and evolve over time.
Groups constantly organize and reorganize into four main patterns: consolidation, clustering, correlation, and ongoing diversity. These patterns are consistent with spatially scattered groups that interact often over time.
In consolidation, individuals’ actions, attitudes, and ideas become more uniform as they engage with one another on a regular basis. The majority’s beliefs propagate across the group, while the minority shrinks.
Clustering happens when group members converse more frequently due to their proximity. Individuals are subject to influence by their closest members, as the law of social impact says, and as a result, clusters of group members with similar beliefs form. Clustering frequently protects minority group members from the majority’s influence. As a result, subgroups can arise that share similar concepts yet diverge from the overall population’s beliefs.
Correlation occurs when individual group members’ opinions on a wide range of issues (including issues that have never been openly discussed before) converge over time, resulting in their opinions becoming correlated.
Minority members in continuing diversity are frequently sheltered from dominant influence by clustering. Diversity exists when the minority group is able to reject majority influence and communicate with majority members. However, if the majority is large or minority members are physically separated from one another, diversity declines.
Contemporary Perspectives
Social impact theory has undergone ongoing evolution, with contemporary analyses emphasizing the dynamic nature of social influence. Researchers now recognize that factors such as social immediacy — the closeness between individuals in a social context — temporal immediacy, referring to the timing of the influence, and physical immediacy, the spatial closeness, play pivotal roles in the strength and direction of social impact.
Helen Harton and colleagues conducted a study in 1998, which looked at the four patterns of dynamic social impact theory. The study involved one big (six rows of 15-30 individuals) and two small basic psychology classrooms (each with one group). Ten questions were picked from the course readings and delivered as handouts, read aloud, or projected on an overhead projector. Students were allowed approximately 1 minute each topic to mark their pre-discussion answers.
The students were then told to talk for 1 or 2 minutes with their neighbours (on either side) about the allotted questions, specifically which response they picked and why. There was little initial variety on two of the questions: one was too simple (the majority got it), and the other was too difficult (the majority agreed on the incorrect answer).
For Consolidation, overall, discussion-induced consolidation occurred in 7 out of the 8 independent groups, indicating majority members converting minority members. Clustering- prior to discussion, neighbours answers were evenly distributed. Post-discussion, groups exhibited a significant degree of spatial clustering, as neighbours influenced each other to become more similar.
In Correlation, there was an increased tendency for an answer on one question to be associated with an answer on another question that was completely unrelated content-wise. Continuing Diversity- none of the 8 groups reached unanimity on any of the questions – meaning, minority group members did not completely conform to majority group members.
In the digital age, the theory helps to analyze how individuals are influenced by the presence of others online. Communication methods have evolved, with an online behavior pattern that underlines the power of social proof in digital interactions. Empirical study in the context of social media has discovered evidence supporting the effects of the number of sources (i.e. likes) on performance outcomes such as box office sales.
In a 2016 study, Babajide Osatuyi and Katia Passerini used Social Network Analysis centrality indicators, such as betweenness, closeness, and degree centralities, to test two of the laws outlined in social impact theory. They investigated the impact of using Twitter and discussion boards in a learning management system (e.g., Moodle and Blackboard) on student performance, as evaluated by the final grade in a course.
Their findings corroborate the first law, which states that the social impact is a multiplicative outcome of strength, immediacy, and the number of encounters between students. This study also revealed some intriguing observations that educators should consider when integrating new social technologies into pedagogy.
Contemporary perspectives have extended the original theory, posing models that account for a more complex and fluid dynamic. These models recognize that:
Influence is not static; it evolves as groups and societies change.
Individuals’ responses to social influence can lead to new, emergent patterns in group dynamics.
Through these contemporary lenses, Social Impact Theory remains a critical framework for understanding social phenomena, albeit with the recognition that any simplistic application falls short of capturing the rich tapestry of human social interactions.
References:
- Asch, S. E. (1952) Social psychology. Englewood Cliffs, N.J.: Prentice-Hall
- Ding, C.; Cheng, H. K.; Duan, Y.; Jin, Y. (2017). The power of the “like” button: The impact of social media on box office. Decision Support Systems. 94: 77–84. doi: 10.1016/j.dss.2016.11.002
- Forsyth, D.R. (2009). Group dynamics: New York: Wadsworth
- Gerard, H. B., Wilhelmy, R. A., & Conolley, E. S. (1968) Conformity and group size. Journal of Personality and Social Psychology, 8, 79-82
- Harton, Helen & Brown, Laura & Jackson, Craig & Latane, Bibb. (1998). Demonstrating Dynamic Social Impact: Consolidation, Clustering, Correlation, and (Sometimes) the Correct Answer. Teaching of Psychology 25. 31-35. 10.1207/s15328023top2501_9.
- Kassin, Fein; Markus, Burke (2013). Social Psychology. Toronto: Nelson Education
- Latane, B., & Harkins, S. (1976) Cross-modality matches suggest anticipated stage fright a multiplicative power function of audience size and status. Perception & Psychophysics, 20, 482-488
- Latané, B (1981). The psychology of social impact. American Psychologist. 36 (4): 343–356. doi: 10.1037/0003-066X.36.4.343
- Latané, Bibb (1996). Dynamic Social Impact: The Creation of Culture by Communication. Journal of Communication. 46 (4): 13–25. doi: 10.1111/j.1460-2466.1996.tb01501.x
- Milgram, Stanley & Bickman, Leonard & Berkowitz, Lawrence. (1969). Note on the Drawing Power of Crowds of Different Size. Journal of Personality and Social Psychology. 13. 79-82. 10.1037/h0028070.
- Osatuyi, B; Passerini, K. (2016). Twittermania: Understanding how social media technologies impact engagement and academic performance of a new generation of learners. Communications of the Association for Information Systems. 39: 509–528. doi: 10.17705/1CAIS.03923