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Estimating the number of communities in a network

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SNAW05 - Bayesian methods for networks

Community detection has been a main topic in the analysis of networks. While there exist a range of powerful and flexible methods for dividing a network into a specified number of communities, it is an open question how to determine exactly how many communities one should use. We answer this question based on a combination of methods from Bayesian analysis and statistical physics. We demonstrate the approach on a range of real-world examples with known community structure, finding that it is able to determine the number of communities correctly in every case.  

This is joint work with Mark Newman (University of Michigan) 

This talk is part of the Isaac Newton Institute Seminar Series series.

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