Community Structure in Time-Dependent, Multiscale, and Multiplex Networks
Abstract
Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly-connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows one to study community structure in a very general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.
Cite
@article{arxiv.0911.1824,
title = {Community Structure in Time-Dependent, Multiscale, and Multiplex Networks},
author = {Peter J. Mucha and Thomas Richardson and Kevin Macon and Mason A. Porter and Jukka-Pekka Onnela},
journal= {arXiv preprint arXiv:0911.1824},
year = {2010}
}
Comments
31 pages, 3 figures, 1 table. Includes main text and supporting material. This is the accepted version of the manuscript (the definitive version appeared in Science), with typographical corrections included here