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Professor Ben Zhao has received a three-year, $499,992 grant from the National Science Foundation (NSF) to pursue research on analyzing and modeling social network structure, growth, and dynamics. The grant also includes Prof. Heather Zheng as co-principal investigator.

Online social networks (OSNs) such as Facebook and LinkedIn are valuable infrastructures for communication and interactions between a large volume of Internet users.  For years, researchers have been trying to answer fundamental questions about the formation of these complex networks, their ongoing evolution, formation of internal structures, and change at different time scales.  Since answering these questions requires real dynamic datasets at scale, most prior studies have been significantly constrained by a lack of data.  Prof. Zhao and Zheng have been granted access by an OSN provider to a uniquely detailed and complete trace of dynamics over 2+ years of a social network.  Their goal is to mine and analyze traces of network dynamics to validate existing models and guide new models for fine grain network dynamics. Objectives include analysis of the preferential attachment model at different stages of network growth, developing new models of network dynamics at fine granularity in both time and graph topology, and explorations of applications driven by novel metrics of graph dynamics.

This work has the potential to dramatically change our understanding of dynamics in online social networks. By taking an empirical, data-driven approach to network modeling, the research can shed light on how traditional models of network dynamics deviate from ground truth. In addition, Zhao and Zheng are developing empirical models that are more effective at accurately predicting network events at small scales.