Sunbelt XXXI International Network for Social Network ... - INSNA

An Agent‐based Approach To Evaluating The Performance Characteristics Of Regression For Distinguishing Longitudinal Network Effects: Pragmatic LessonsIwashyna, Theodore J.; Hutchins, Meghan; Gebremariam, Cham; Lee, Joyce M.Empirical Large‐N NetworksHomophily, Agent Based Models, epidemiology, InfluenceSUN.AM2Background: Using panel data to evaluate network effects on populations has grown in popularity, particularly the use of GEE models at the dyadic level,incorporating lagged effects, to distinguish homophily from network influence. Objective: A regression can be seen as a test attempting to discern theunderlying structure. We evaluated the measurement characteristics of the GEE approach. Methods: We developed an agent‐based model (ABM) withnetwork influence on an observable characteristic and/or homophily in network formation on that characteristic. We repeatedly simulated a panel of datawith the ABM, then analyzed it using the GEE. We examined the sensitivity and specificity across 1,000 separate simulated populations for each condition.Results: (1) If the underlying population had secular trends in the observable characteristic, GEE models without control for such trends will report statisticallysignificant network homophily and influence even when there are no such effects in the underlying population. (2) If the underlying population had networkinfluence, the GEE models were able to detect this with 100% sensitivity. In 9% of cases where there was not network influence, the network influencecoefficients were still statistically significant, independent of homophily. (3) The GEE models had no ability to distinguish situations in which homophily waspresent from situations in which it was not. Conclusions: GEE models show promise, but have clear limits.An Agent‐based Simulation Of Relational MobilityLu, Philip S.Simulation and Agent Based ModelsCulture, Agent Based Models, Network Models, Psychological Network Theory, Relational MobilityFRI.PM1Cross‐cultural psychologists have suggested that differences in behavior among societies may be influenced not only by actor preferences, but also by thedynamics of social network structure. Compared to individuals in the United States, Japanese individuals are more likely to disclose less personal information tothose in their networks (Schug, Yuki, Maddux 2010), choose comforming strategies (Yamagishi, Hashimoto, Schug, 2010), and exhibit less homophily with thosein their social networks (Schug, Yuki, Horikawa, Takemura 2009). In these studies, researchers attribute these differences to the the concept of relationalmobility, or the opportunties to drop and form new connections in a network. In this study, I present a network simulation model where agents take on avariety of friendship formation strategies. I show that the rate at which connections are formed and dropped is more dependent on the initial networkstructure than on individual desires for new connections. The results support the idea that cultural differences may be based on structure, not individualpreferences.