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Detecting profilable and overlapping communities with user-generated multimedia contents in LBSNs

Published: 27 December 2013 Publication History

Abstract

In location-based social networks (LBSNs), users implicitly interact with each other by visiting places, issuing comments and/or uploading photos. These heterogeneous interactions convey the latent information for identifying meaningful user groups, namely social communities, which exhibit unique location-oriented characteristics. In this work, we aim to detect and profile social communities in LBSNs by representing the heterogeneous interactions with a multimodality nonuniform hypergraph. Here, the vertices of the hypergraph are users, venues, textual comments or photos and the hyperedges characterize the k-partite heterogeneous interactions such as posting certain comments or uploading certain photos while visiting certain places. We then view each detected social community as a dense subgraph within the heterogeneous hypergraph, where the user community is constructed by the vertices and edges in the dense subgraph and the profile of the community is characterized by the vertices related with venues, comments and photos and their inter-relations. We present an efficient algorithm to detect the overlapped dense subgraphs, where the profile of each social community is guaranteed to be available by constraining the minimal number of vertices in each modality. Extensive experiments on Foursquare data well validated the effectiveness of the proposed framework in terms of detecting meaningful social communities and uncovering their underlying profiles in LBSNs.

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications
ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 10, Issue 1
December 2013
166 pages
ISSN:1551-6857
EISSN:1551-6865
DOI:10.1145/2559928
Issue’s Table of Contents
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Publication History

Published: 27 December 2013
Accepted: 01 March 2013
Revised: 01 February 2013
Received: 01 August 2012
Published in TOMM Volume 10, Issue 1

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  1. Location-based social networks
  2. community detection
  3. community profiling
  4. heterogeneous hypergraph

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