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Discovering Temporal Communities from Social Network Documents
2007
Seventh IEEE International Conference on Data Mining (ICDM 2007)
This paper studies the discovery of communities from social network documents produced over time, addressing the discovery of temporal trends in community memberships. We first formulate static community discovery at a single time period as a tripartite graph partitioning problem. Then we propose to discover the temporal communities by threading the statically derived communities in different time periods using a new constrained partitioning algorithm, which partitions graphs based on topology
doi:10.1109/icdm.2007.56
dblp:conf/icdm/ZhouCZG07
fatcat:sbo7ezh4vvbs5m4x2wghf4pbua