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Comparing Two Local Methods for Community Detection in Social Networks
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SYSNO ASEP 0386764 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Comparing Two Local Methods for Community Detection in Social Networks Author(s) Zehnalova, S. (CZ)
Kudělka, Miloš (UTIA-B) RID
Kudělka, M. (CZ)
Snášel, V. (CZ)Number of authors 4 Source Title Proceedings of the 2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN). - Piscataway : IEEE, 2012 - ISBN 978-1-4673-4793-8 Pages s. 1-6 Number of pages 6 s. Publication form Print - P Action CASoN 2012. International Conference on Computational Aspects of Social Networks /4./ Event date 21.11.2012-23.11.2012 VEvent location Sao Carlos Country BR - Brazil Event type WRD Language eng - English Country US - United States Keywords social networks ; community detection ; DBLP Subject RIV BD - Theory of Information Institutional support UTIA-B - RVO:67985556 UT WOS 000314803000027 DOI https://doi.org/10.1109/CASoN.2012.6412395 Annotation One of the most obvious features of social networks is their community structure. Several types of methods were developed for discovering communities in the networks, either from the global perspective or based on local information only. Local methods are appropriate when working with large and dynamic networks or when real-time results are expected. In this paper we explore two such methods and compare the results obtained on the sample of a co-authorship network.We study how much may detected communities vary according to the method used for computation. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2013
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