Measuring the influence of network structures on social interaction over time

Abstract

Communication decisions in networks can be described as a two-level decision process. The second decision about event receivers is a multinomial logistic regression model with an unknown vector of parameters. These parameters evaluate network structures that enforce or weaken the probability for choosing certain actors. However, in many cases those parameters may change over time. In this paper a sliding window approach is introduced, that can be used to understand whether there is evolution of behavior in an observed data set. For future work, it is proposed to develop a statistical test on normalized decision statistics. © 2012 Springer-Verlag Berlin Heidelberg.