A Fast Algorithm to Find Overlapping Communities in Networks
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A microscopic view on community detection in complex networks
Proceedings of the 2nd PhD workshop on Information and knowledge management
Mapping search relevance to social networks
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
Topological tree clustering of social network search results
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
A multi-resolution approach to learning with overlapping communities
Proceedings of the First Workshop on Social Media Analytics
Challenger, a new way to visualize data
GD'11 Proceedings of the 19th international conference on Graph Drawing
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Proceedings of the 21st international conference on World Wide Web
Line orthogonality in adjacency eigenspace with application to community partition
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Tripartite community structure in social bookmarking data
The New Review of Hypermedia and Multimedia - Special issue on Social Linking and Hypermedia
iTop: interaction based topic centric community discovery on twitter
Proceedings of the 5th Ph.D. workshop on Information and knowledge
An O(n2) algorithm for detecting communities of unbalanced sizes in large scale social networks
Knowledge-Based Systems
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International Journal of Artificial Life Research
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SocInfo'12 Proceedings of the 4th international conference on Social Informatics
GD'12 Proceedings of the 20th international conference on Graph Drawing
Density-based Community Identification and Visualisation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
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Computers and Operations Research
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Personal and Ubiquitous Computing
Hierarchical Social Network Analysis Using a Multi-Agent System: A School System Case
International Journal of Agent Technologies and Systems
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Community analysis algorithm proposed by Clauset, Newman, and Moore (CNM algorithm) finds community structure in social networks. Unfortunately, CNM algorithm does not scale well and its use is practically limited to networks whose sizes are up to 500,000 nodes. We show that this inefficiency is caused from merging communities in unbalanced manner and that a simple heuristics that attempts to merge community structures in a balanced manner can dramatically improve community structure analysis. The proposed techniques are tested using data sets obtained from existing social networking service that hosts 5.5 million users. We have tested three three variations of the heuristics. The fastest method processes a SNS friendship network with 1 million users in 5 minutes (70 times faster than CNM) and another friendship network with 4 million users in 35 minutes, respectively. Another one processes a network with 500,000 nodes in 50 minutes (7 times faster than CNM), finds community structures that has improved modularity, and scales to a network with 5.5 million.