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 timepoints
in such streams of graphs, in an on-line, any-time
fashion? We propose GraphScope, that addresses both problems,
using information theoretic principles. Contrary to the
majority of earlier methods, it needs no user-defined parameters.
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 several
diverse domains. In all cases it produces meaningful
time-evolving patterns that agree with human intuition.