Abstract
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.
Highlights
What determines the adoption of beliefs, new technologies, cultural behaviors, and cooperation among human agents? These are all questions of social learning, a term that refers broadly to the processes by which a person’s social environment shapes their actions and cognitions
This paper contributes to our understanding of social learning and network evolution through the analysis of a large mobile contact network, coupled with data on the tastes of individuals, over two points in time
The result that “love of the same” is a basis for network formation is consistent with many other studies of homophily in social networks—here we demonstrate that this phenomenon applies to the addition of new mobile device contacts in a large, complex network
Summary
What determines the adoption of beliefs, new technologies, cultural behaviors, and cooperation among human agents? These are all questions of social learning, a term that refers broadly to the processes by which a person’s social environment shapes their actions (how a person behaves) and cognitions (how a person thinks). A one-month time interval was chosen so that we might observe short-term changes in the network—giving us a view of what might be thought of as the “first derivative” of the longer-term changes in attributes and social networks over time Included in this analysis are all mobile platform users in the United States with taste data in a given month—this excludes all users who either had no recorded activity, as well as those users who used their privacy settings to prevent tracking of their usage history. These characteristics are typical for communication networks among mobile phone users [73, 74] These data are used to fit statistical models that test our hypotheses about how attribute similarity (or difference) influences tie formation (or deletion), and how tie structures influence changes in tastes. The following sections provide more detail on the precise functional forms used to test our three hypotheses
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
