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This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals’ access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends. [ABSTRACT FROM AUTHOR]

Both classical social psychological theories and recent formal models of opinion differentiation and bi-polarization assign a prominent role to negative social influence. Negative influence is defined as shifts away from the opinion of others and hypothesized to be induced by discrepancy with or disliking of the source of influence. There is strong empirical support for the presence of positive social influence (a shift towards the opinion of others), but evidence that large opinion differences or disliking could trigger negative shifts is mixed. We examine positive and negative influence with controlled exposure to opinions of other individuals in one experiment and with opinion exchange in another study. Results confirm that similarities induce attraction, but results do not support that discrepancy or disliking entails negative influence. Instead, our findings suggest a robust positive linear relationship between opinion distance and opinion shifts. [ABSTRACT FROM AUTHOR]

Fashion is an essential part of human experience and an industry worth over $1.7 trillion. Important choices such as hiring or dating someone are often based on the clothing people wear, and yet we understand almost nothing about the objective features that make an outfit fashionable. In this study, we provide an empirical approach to this key aesthetic domain, examining the link between color coordination and fashionableness. Studies reveal a robust quadratic effect, such that that maximum fashionableness is attained when outfits are neither too coordinated nor too different. In other words, fashionable outfits are those that are moderately matched, not those that are ultra-matched (“matchy-matchy”) or zero-matched (“clashing”). This balance of extremes supports a broader hypothesis regarding aesthetic preferences–the Goldilocks principle–that seeks to balance simplicity and complexity. [ABSTRACT FROM AUTHOR]