Beyond Homophily: Incorporating Actor Variables in Actor-oriented Network Models (1803.07172v2)

Abstract: We consider the specification of effects of numerical actor attributes in statistical models for directed social networks. A fundamental mechanism is homophily or assortativity, where actors have a higher likelihood to be tied with others having similar values of the variable under study. But there are other mechanisms that may also play a role in how the attribute values of two actors influence the likelihood of a tie. We discuss three additional mechanisms: aspiration to send ties to others having high values; conformity in the sense of sending more ties to others whose values are close to what may be considered the `social norm'; and sociability, where those having higher values will tend to send more ties generally. These mechanisms may operate jointly, and then their effects will be confounded. We present a specification representing these effects simultaneously by a four-parameter quadratic function of the values of sender and receiver. Greater flexibility can be obtained by a five-parameter extension. We argue that empirical researchers often overlook the possibility that homophily may be confounded with these other mechanisms, and that for actor attributes that have important effects on directed networks, these specifications may provide an improvement. An illustration is given of the dependence of advice ties on academic grades in a network of MBA students, analyzed by the Stochastic Actor-oriented Model.