University of Birmingham > Talks@bham > Combinatorics and Probability Seminar > Sampling sufficiency for determining modularity.

Sampling sufficiency for determining modularity.

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  • UserFiona Skerman (University of Bristol)
  • ClockThursday 16 January 2020, 15:00-16:00
  • HouseWatson LTC.

If you have a question about this talk, please contact Richard Montgomery.

Modularity is used in popular algorithms for community detection. For a given network G, each partition of the vertices has a modularity score, with higher values indicating that the partition better captures community structure in G. The (max) modularity q of the network G is defined to be the maximum over all vertex partitions of the modularity score, and satisfies 0 ≤ q(G) ≤ 1.

We analyse when community structure of an underlying network can be determined from its observed network. In a natural model where we suppose edges in an underlying graph G appear with some probability in our observed graph G’ we describe how high a sampling probability we need to infer the community structure of the underlying network.

Joint work with Colin McDiarmid.

This talk is part of the Combinatorics and Probability Seminar series.

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