Modularity for heterogeneous networks
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Detecting overlapping communities in folksonomies
Proceedings of the 23rd ACM conference on Hypertext and social media
Identifying Overlying Group of People through Clustering
International Journal of Information Technology and Web Engineering
OverCite: finding overlapping communities in citation network
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Online folksonomies are modeled as tripartite hypergraphs, and detecting communities from such networks is a challenging and well-studied problem. However, almost every existing algorithm known to us for community detection in hypergraphs assign unique communities to nodes, whereas in reality, nodes in folksonomies belong to multiple overlapping communities e.g. users have multiple topical interests, and the same resource is often tagged with semantically different tags. In this paper, we propose an algorithm to detect overlapping communities in folksonomies by customizing a recently proposed edge-clustering algorithm (that is originally for traditional graphs) for use on hypergraphs.