A dual assortative measure of community structure
Data Analysis, Statistics and Probability
2008-01-23 v1 Physics and Society
Abstract
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.
Cite
@article{arxiv.0801.3290,
title = {A dual assortative measure of community structure},
author = {Todd D. Kaplan and Stephanie Forrest},
journal= {arXiv preprint arXiv:0801.3290},
year = {2008}
}