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Reconstruction of Missing Data in Social Networks Based on Temporal Patterns of Interactions

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A. Stomakhin, M. Short, and A. Bertozzi. Reconstruction of Missing Data in Social Networks Based on Temporal Patterns of Interactions. Inverse Problems 2011.



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.