We discuss a mathematical framework based on a self-exciting point
process aimed at analyzing temporal patterns in the series of interaction events
between agents in a social network. We then develop a reconstruction model
that allows one to predict the unknown participants in a portion of those events.
Finally, we apply our results to the Los Angeles gang network.
The paper has been selected by the editors of Inverse Problems for inclusion in the "Highlights of 2011" collection. View certificate.