2007 AFrameworkforCommunityIdentific

• (Tantipathananandh et al., 2007) ⇒ Chayant Tantipathananandh, Tanya Berger-Wolf, and David Kempe. (2007). “A Framework for Community Identification in Dynamic Social Networks.” In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge discovery and data mining. ISBN:978-1-59593-609-7 doi:10.1145/1281192.1281269

Subject Headings: Community Structure, Dynamic Graph Data Mining.

Cited By

• http://scholar.google.com/scholar?q=%222007%22+A+Framework+for+Community+Identification+in+Dynamic+Social+Networks
• http://dl.acm.org/citation.cfm?id=1281192.1281269&preflayout=flat#citedby

Quotes

Abstract

We propose frameworks and algorithms for identifying communities in social networks that change over time. Communities are intuitively characterized as "unusually densely knit" subsets of a social network. This notion becomes more problematic if the social interactions change over time. Aggregating social networks over time can radically misrepresent the existing and changing community structure. Instead, we propose an optimization-based approach for modeling dynamic community structure. We prove that finding the most explanatory community structure is NP-hard and APX-hard, and propose algorithms based on dynamic programming, exhaustive search, maximum matching, and greedy heuristics. We demonstrate empirically that the heuristics trace developments of community structure accurately for several synthetic and real-world examples.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2007 AFrameworkforCommunityIdentific	David Kempe Chayant Tantipathananandh Tanya Berger-Wolf			A Framework for Community Identification in Dynamic Social Networks				10.1145/1281192.1281269		2007