A dual assortative measure of community structure

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Current community detection algorithms operate by optimizing a statistic called modularity, which analyzes the distribution of positively weighted edges in a network. Modularity does not account for negatively weighted edges. This paper introduces a dual assortative modularity measure (DAMM) that incorporates both positively and negatively weighted edges. We describe the the DAMM statistic and illustrate its utility in a community detection algorithm. We evaluate the efficacy of the algorithm on both computer generated and real-world networks, showing that DAMM broadens the domain of networks that can be analyzed by community detection algorithms.

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Data Analysis, Statistics and Probability, Physics and Society

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http://salesiana.dossiersoluciones.com/handle/123456789/146384

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0801.3290
 http://arxiv.org/abs/0801.3290

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arXiv