Finding a wise group of experts in social networks

Yin, Hongzhi, Cui, Bin and Huang, Yuxin (2011). Finding a wise group of experts in social networks. In: Jie Tang, Irwin King, Ling Chen and Jianyong Wang, Advanced Data Mining and Applications. 7th International Conference, ADMA 2011. Proceedings, Part I. ADMA 2011: 7th International Conference on Advanced Data Mining and Applications, Beijing, China, (381-394). 17-19 December, 2011. doi:10.1007/978-3-642-25853-4_29


Author Yin, Hongzhi
Cui, Bin
Huang, Yuxin
Title of paper Finding a wise group of experts in social networks
Conference name ADMA 2011: 7th International Conference on Advanced Data Mining and Applications
Conference location Beijing, China
Conference dates 17-19 December, 2011
Proceedings title Advanced Data Mining and Applications. 7th International Conference, ADMA 2011. Proceedings, Part I   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Series Lecture Notes in Artificial Intelligence
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2011
Sub-type Fully published paper
DOI 10.1007/978-3-642-25853-4_29
ISBN 9783642258527
9783642258534
ISSN 0302-9743
1611-3349
Editor Jie Tang
Irwin King
Ling Chen
Jianyong Wang
Volume 7120
Start page 381
End page 394
Total pages 14
Chapter number 29
Total chapters 31
Language eng
Formatted Abstract/Summary
Given a task T, a pool of experts χ with different skills, and a social network G that captures social relationships and various interactions among these experts, we study the problem of finding a wise group of experts χ′, a subset of χ′, to perform the task. We call this the Expert Group Formation problem in this paper. In order to reduce various potential social influence among team members and avoid following the crowd, we require that the members of χ′ not only meet the skill requirements of the task, but also be diverse. To quantify the diversity of a group of experts, we propose one metric based on the social influence incurred by the subgraph in G that only involves χ′. We analyze the problem of Diverse Expert Group Formation and show that it is NP-hard. We explore its connections with existing combinatorial problems and propose novel algorithms for its approximation solution. To the best of our knowledge, this is the first work to study diversity in the social graph and facilitate its effect in the Expert Group Formation problem. We conduct extensive experiments on the DBLP dataset and the experimental results show that our framework works well in practice and gives useful and intuitive results.
Keyword Team formation
Social influence
Social network
Heuristics algorithm
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 01 Mar 2015, 22:09:24 EST by Hongzhi Yin on behalf of School of Information Technol and Elec Engineering