Graphscope: parameter-free mining of large time-evolving graphs

How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity time-points in such streams of graphs, in an on-line, any-time fashion? We propose GraphScope, that addresses both prob-lems, using information theoretic principles. Contrary to the majority of earlier methods, it needs no user-defined param-eters. Moreover, it is designed to operate on large graphs, in a streaming fashion. We demonstrate the efficiency and effectiveness of our GraphScope on real datasets from sev-eral diverse domains. In all cases it produces meaningful time-evolving patterns that agree with human intuition