Finding Experts Using Social Network Analysis

• Published in: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence pp. 77 - 80
• Main Authors: Fu, Yupeng, Xiang, Rongjing, Liu, Yiqun, Zhang, Min, Ma, Shaoping
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 02.11.2007
• Series: ACM Conferences
• Subjects: Human-centered computing > Collaborative and social computing; Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Web-based interaction; Information systems > Information retrieval; Information systems > Information storage systems > Storage architectures > Storage network architectures; Information systems > World Wide Web > Web applications; Information systems > World Wide Web > Web services
• ISBN: 0769530265; 9780769530260
• DOI: 10.1109/WI.2007.59

Searching an organization's document repositories for experts is a frequently occurred problem in intranet information management. A common method for finding experts in an organization is to use social networks -people are not isolated but connected by various kinds of associations. In organizations, people explicitly send email to one another thus social networks are likely to be contained in the patterns of communication. Moreover, in some web pages, the relationship among people is also recorded. In our approach we propose several strategies in discovering the associations among people from emails and web pages. Based on the social networks, we proposed an expertise propagation algorithm: from a ranked list of candidates according to their probability of being expert for a certain topic, we select a small set of the top ones as seed, and then use the social networks among the candidates to discover other potential experts. The experiments on TREC enterprise track show significant performance improvement with the algorithm.