Simulate to Detect: A Multi-agent System for Community Detection

Community detection in social networks is a well-known problem encountered in many fields. Many traditional algorithms have been proposed to solve it, with recurrent problems: impossibility to deal with dynamic networks, sensitivity to noise, no detection of overlapping communities, exponential runn...

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Bibliographic Details
Published in2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Vol. 2; pp. 402 - 408
Main Authors Cazabet, R., Amblard, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2011
Subjects
Benchmark testing
Communities
Community detection
Complexity theory
Dynamic networks
Facebook
Image edge detection
Multi-agent simulation
Multiagent systems
Social Networks
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ISBN9781457713736
145771373X
DOI10.1109/WI-IAT.2011.50

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Summary:Community detection in social networks is a well-known problem encountered in many fields. Many traditional algorithms have been proposed to solve it, with recurrent problems: impossibility to deal with dynamic networks, sensitivity to noise, no detection of overlapping communities, exponential running time. This paper proposes a multi-agent system that replays the evolution of a network and, in the same time, reproduces the rise and fall of communities. After presenting the strengths and weaknesses of existing community detection algorithms, we describe the multi-agent system we propose. Then, we compare our solution with existing works, and show some advantages of our method, in particular the possibility to dynamically detect the communities.
ISBN:9781457713736
145771373X
DOI:10.1109/WI-IAT.2011.50