Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

Details Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

2010-12-06

arxiv.org/abs/1012.1269v1

Journal of Statistical Mechanics: Theory and Experiment (2011) P01023

Physics

Data Analysis, Statistics and Probability

25 pages, 10 figures

Scientific paper

10.1088/1742-5468/2011/01/P01023

We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This analytic procedure is not only more exact than its numerical alternatives such as LFM and GCE but also much faster. Critical resolution levels can be identified by searching for intervals in which large changes of the resolution do not lead to growth of communities. We tested our algorithm on benchmark graphs and on a network of 492 papers in information science. Combined with a specific post-processing, the algorithm gives much more precise results on LFR benchmarks with high overlap compared to other algorithms and performs very similar to GCE.

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