A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks

摘要

This paper introduces an integrated adaptive temporalcausal network model for dynamics in networks of social interactions addressing contagion between states, and changing connections within these social networks by two principles: the homophily principle and the more-becomes-more principle. The model has been evaluated in three different manners: by simulation experiments, by verification based on mathematical analysis, and by validation against an empirical data set.