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An Evaluation of Community Detection Algorithms on Large-Scale Email Traffic

Farnaz Moradi (Institutionen för data- och informationsteknik, Nätverk och system (Chalmers) ) ; Tomas Olovsson (Institutionen för data- och informationsteknik, Nätverk och system (Chalmers) ) ; Philippas Tsigas (Institutionen för data- och informationsteknik, Nätverk och system, Datakommunikation och distribuerade system (Chalmers))
Proceedings of the 11th International Symposium on Experimental Algorithms,, SEA 2012, Bordeaux, France, June 7-9, 2012. p. 283-294. (2012)
[Konferensbidrag, refereegranskat]

Community detection algorithms are widely used to study the structural properties of real-world networks. In this paper, we experimentally evaluate the qualitative performance of several community detection algorithms using large-scale email networks. The email networks were generated from real email traffic and contain both legitimate email (ham) and unsolicited email (spam). We compare the quality of the algorithms with respect to a number of structural quality functions and a logical quality measure which assesses the ability of the algorithms to separate ham and spam emails by clustering them into distinct communities. Our study reveals that the algorithms that perform well with respect to structural quality, don’t achieve high logical quality. We also show that the algorithms with similar structural quality also have similar logical quality regardless of their approach to clustering. Finally, we reveal that the algorithm that performs link community detection is more suitable for clustering email networks than the node-based approaches, and it creates more distinct communities of ham and spam edges.

Nyckelord: Community detection, Email networks, Quality functions

Denna post skapades 2012-06-11. Senast ändrad 2015-12-17.
CPL Pubid: 158755


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