Evolve: Analyzing Evolving Social Networks.

摘要

Many current social network analytic methods work by analyzing a static aggregate graph, which provides a limited view of the structure and behavior of real-world social networks. Social networks in reality are dynamic and evolve over time as people join or leave the networks and new connections form. This work investigates developing dynamic social network analysis (DSNA) methods to explicitly model time and heterogeneity. It focuses on two objectives: (1) Dynamic SNA metrics and methods which take time into account; (2) Predictive methods for modeling and predicting how individuals and groups change over time.