Detecting network communities by propagating labels under constraints

Details Detecting network communities by propagating labels under constraints Detecting network communities by propagating labels under constraints

2009-03-18

arxiv.org/abs/0903.3138v2

Phys. Rev. E 80(2): 026129 (2009)

Physics

Data Analysis, Statistics and Probability

16 pages, 3 figures, 6 tables; significant expansion of discussion of results

Scientific paper

10.1103/PhysRevE.80.026129

We investigate the recently proposed label-propagation algorithm (LPA) for identifying network communities. We reformulate the LPA as an equivalent optimization problem, giving an objective function whose maxima correspond to community solutions. By considering properties of the objective function, we identify conceptual and practical drawbacks of the label propagation approach, most importantly the disparity between increasing the value of the objective function and improving the quality of communities found. To address the drawbacks, we modify the objective function in the optimization problem, producing a variety of algorithms that propagate labels subject to constraints; of particular interest is a variant that maximizes the modularity measure of community quality. Performance properties and implementation details of the proposed algorithms are discussed. Bipartite as well as unipartite networks are considered.

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