Comparing Two Local Methods for Community Detection in Social Networks

被引：0

作者：

Zehnalova, Sarka ^{[1
]}

Kudelka, Milos, Jr. ^{[2
]}

Kudelka, Milos ^{[1
]}

Snasel, Vaclav ^{[1
]}

机构：

[1] VSB Tech Univ Ostrava, 17 Listopadu 15, Ostrava 70833, Czech Republic

[2] Inst Informat Theory & Automat, Prague 18208, Czech Republic

来源：

2012 FOURTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL ASPECTS OF SOCIAL NETWORKS (CASON) | 2012年

关键词：

social networks; community detection; DBLP;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：155 / 160

页数：6

共 25 条

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