Constant communities in complex networks

Tanmoy Chakraborty, Sriram Srinivasan, Niloy Ganguly, Sanjukta Bhowmick, Animesh Mukherjee

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Identifying community structure is a fundamental problem in network analysis. Most community detection algorithms are based on optimizing a combinatorial parameter, for example modularity. This optimization is generally NP-hard, thus merely changing the vertex order can alter their assignments to the community. However, there has been less study on how vertex ordering influences the results of the community detection algorithms. Here we identify and study the properties of invariant groups of vertices (constant communities) whose assignment to communities are, quite remarkably, not affected by vertex ordering. The percentage of constant communities can vary across different applications and based on empirical results we propose metrics to evaluate these communities. Using constant communities as a pre-processing step, one can significantly reduce the variation of the results. Finally, we present a case study on phoneme network and illustrate that constant communities, quite strikingly, form the core functional units of the larger communities.

Original languageEnglish (US)
Article number1825
JournalScientific reports
Volume3
DOIs
StatePublished - 2013

ASJC Scopus subject areas

  • General

Cite this

Chakraborty, T., Srinivasan, S., Ganguly, N., Bhowmick, S., & Mukherjee, A. (2013). Constant communities in complex networks. Scientific reports, 3, [1825]. https://doi.org/10.1038/srep01825