Christos Faloutsos
ABSTRACT
How do graphs look like? How do they evolve over time? How can we generate realistic-looking graphs? We review some static and temporal 'laws', and we describe the ``Kronecker'' graph generator, which naturally matches all of the known properties of real graphs. We also describe some case studies.
The first is on influence and virus propagation on real graphs, where we show that the so-called ``epidemic threshold'' of a graph depends only on the first eigenvalue of the adjacency matrix. The second shows how to spot patterns in e-bay interaction graphs, indicative of the ``non-delivery'' type of fraud. The last is analysis on blog cascades and some surprising patterns there.
Index Terms
- Graph mining and influence propagation
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