2008/08/20 by Philipp Schuetz, Amedeo Caflisch
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #Peer-to-Peer Network Technologies #cond-mat.dis-nn #cs.DS #physics.soc-ph #q-bio.MN #q-bio.QM
paper · pdf · doi:10.1103/physreve.78.026112
published as Phys. Rev. E 78, 026112 (2008) · 17 pages, 2 figures
openalex publication_date 2008/08/20 · arxiv created 2008/09/25 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We have recently introduced a multistep extension of the greedy algorithm for modularity optimization. The extension is based on the idea that merging l pairs of communities (l>1) at each iteration prevents premature condensation into few large communities. Here, an empirical formula is presented for the choice of the step width l that generates partitions with (close to) optimal modularity for 17 real-world and 1100 computer-generated networks. Furthermore, an in-depth analysis of the communities of two real-world networks (the metabolic network of the bacterium E. coli and the graph of coappearing words in the titles of papers coauthored by Martin Karplus) provides evidence that the partition obtained by the multistep greedy algorithm is superior to the one generated by the original greedy algorithm not only with respect to modularity, but also according to objective criteria. In other words, the multistep extension of the greedy algorithm reduces the danger of getting trapped in local optima of modularity and generates more reasonable partitions.