Community evolution detection in time-evolving information networks

In this paper, we propose a framework for representing, modeling and mining time-evolving information networks. Our framework introduces a graph-based model-theoretic approach to represent such networks and how they change over time. Also, we provide a method for supporting matching-based community evolution detection in time-evolving information networks, by identifying several classes of community transitions, along with algorithms that implement them. © 2013 ACM.