2012/01/16 by Erwan Le Martelot, Martelot, Erwan Le, Chris Hankin +1
Computer Science · Physics and Astronomy · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #cs.DS #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1201.3307
This paper is an extension of the paper named "Multi-scale Community Detection using Stability as Optimisation Criterion in a Greedy Algorithm" by the same authors published in Proc. of the 2011 Int. Conf. on Knowledge Discovery and Information Retrieval (KDIR 2011), SciTePress, 2011, 216-225
arxiv created 2012/01/16 · arxiv updated 2015/03/19
Many real systems can be represented as networks whose analysis can be very informative regarding the original system's organisation. In the past decade community detection received a lot of attention and is now an active field of research. Recently stability was introduced as a new measure for partition quality. This work investigates stability as an optimisation criterion that exploits a Markov process view of networks to enable multi-scale community detection. Several heuristics and variations of an algorithm optimising stability are presented as well as an application to overlapping communities. Experiments show that the method enables accurate multi-scale network analysis.