Abstract

A cognitive model of social influence (Social Sampling Theory [SST]) is developed and applied to several social network phenomena including polarization and contagion effects. Social norms and individuals’ private attitudes are represented as distributions rather than the single points used in most models. SST is explored using agent-based modeling to link individual-level and network-level effects. People are assumed to observe the behavior of their social network neighbors and thereby infer the social distribution of particular attitudes and behaviors. It is assumed that (a) people dislike behaving in ways that are extreme within their neighborhood social norm (social extremeness aversion assumption), and hence tend to conform and (b) people prefer to behave consistently with their own underlying attitudes (authenticity preference assumption) hence minimizing dissonance. Expressed attitudes and behavior reflect a utility-maximizing compromise between these opposing principles. SST is applied to a number of social phenomena including (a) homophily and the development of segregated neighborhoods, (b) polarization, (c) effects of norm homogeneity on social conformity, (d) pluralistic ignorance and false consensus effects, (e) backfire effects, (f) interactions between world view and social norm effects, and (g) the opposing effects on subjective well-being of authentic behavior and high levels of social comparison. More generally, it is argued that explanations of social comparison require the variance, not just the central tendency, of both attitudes and beliefs about social norms to be accommodated.

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