Regional subgraph discovery in social networks

Cheng Te Li, Man Kwan Shan, Shou De Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper solves a region-based subgraph discovery problem. We are given a social network and some sample nodes which is supposed to belong to a specific region, and the goal is to obtain a subgraph that contains the sampled nodes with other nodes in the same region. Such regional subgraph discovery can benefit regionbased applications, including scholar search, friend suggestion, and viral marketing. To deal with this problem, we assume there is a hidden backbone connecting the query nodes directly or indirectly in their region. The idea is that individuals belonging to the same region tend to share similar interests and cultures. By modeling such fact on edge weights, we search the graph to extract the regional backbone with respect to the query nodes. Then we can expand the backbone to derive the regional network. Experiments on a DBLP co-authorship network show the proposed method can effectively discover the regional subgraph with high precision scores. Copyright is held by the author/owner(s).

Original languageEnglish
Title of host publicationWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion
Pages563-564
Number of pages2
DOIs
Publication statusPublished - 2012 May 21
Event21st Annual Conference on World Wide Web, WWW'12 - Lyon, France
Duration: 2012 Apr 162012 Apr 20

Publication series

NameWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion

Other

Other21st Annual Conference on World Wide Web, WWW'12
CountryFrance
CityLyon
Period12-04-1612-04-20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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