Communities in networks - a continuous approach

2007/09/06 by Małgorzata J. Krawczyk, Malgorzata J. Krawczyk, Krawczyk, Malgorzata J. +3 · 1 citation
Economics, Econometrics and Finance · Physics and Astronomy · #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Data Analysis #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an) #Theoretical and Computational Physics #physics.data-an #physics.soc-ph

paper · pdf · doi:10.48550/arxiv.0709.0923

11 pages, 7 figures. Figures refined

openalex publication_date 2007/09/06 · arxiv created 2008/01/08 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A system of differential equations is proposed designed as to identify communities in weighted networks. The input is a symmetric connectivity matrix A_ij. A priori information on the number of communities is not needed. To verify the dynamics, we prepared sets of separate, fully connected clusters. In this case, the matrix A has a block structure of zeros and units. A noise is introduced as positive random numbers added to zeros and subtracted from units. The task of the dynamics is to reproduce the initial block structure. In this test, the system outperforms the modularity algorithm, if the number of clusters is larger than four.

Cited by

• Community detection in graphs

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