Networks Evolving Step by Step: Statistical Analysis of Dyadic Event Data

Abstract

With few exceptions, statistical analysis of social networks is currently focused on cross-sectional or panel data. On the other hand, automated collection of network-data often produces event data, i.e., data encoding the exact time of interaction between social actors. In this paper we propose models and methods to analyze such networks of dyadic events and to determine the factors that influence the frequency and quality of interaction. We apply our methods to empirical datasets about political conflicts and test several hypotheses concerning reciprocity and structural balance theory.