Revealing contact patterns among high-school students using maximal cliques in link streams

By Tiphaine Viard, Matthieu Latapy, Clémence Magnien

First International Workshop on Dynamics in Networks (DyNo), in conjunction with ASONAM, 2015.

Abstract

Interaction traces between humans are usually rich in information concerning the patterns and habits of individuals. Such datasets have been recently made available, and more and more researchers address the new questions raised by this data. A link stream is a sequence of triplets (t, u, v) indicating that an interaction occurred between u and v at time t, and as such is a natural representation of these data. We generalize the classical notion of cliques in graphs to such link streams: for a given ∆, a ∆-clique is a set of nodes and a time interval such that all pairs of nodes in this set interact at least every ∆ during this time interval. We proceed to compute the maximal ∆-cliques on a real-world dataset of contact among students, and show how it can bring new interpretation to patterns of contact.

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