DocumentCode :
594892
Title :
A game theory inspired, decentralized, local information based algorithm for community detection in social graphs
Author :
Narayanam, Ramasuri ; Narahari, Y.
Author_Institution :
IBM Res., Bangalore, India
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
1072
Lastpage :
1075
Abstract :
Motivated by the observation that communities in real world social networks form due to actions of rational individuals in networks, we propose a novel game theory inspired algorithm to determine communities in networks. The algorithm is decentralized and only uses local information at each node. We show the efficacy of the proposed algorithm through extensive experimentation on several real world social network data sets.
Keywords :
game theory; graph theory; social sciences computing; community detection; decentralized local information based algorithm; game theory; real world social network data sets; social graphs; Algorithm design and analysis; Clustering algorithms; Communities; Electronic mail; Games; Partitioning algorithms; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460321
Link To Document :
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