DocumentCode :
1973241
Title :
Influence Analysis Based Expert Finding Model and Its Applications in Enterprise Social Network
Author :
Dong Liu ; Li Wang ; Jianhua Zheng ; Ke Ning ; Liang-Jie Zhang
Author_Institution :
Nat. Eng. Res. Center for Supporting Software of Enterprise Internet Services, Kingdee Software (China) Co. Ltd., Shenzhen, China
fYear :
2013
fDate :
June 28 2013-July 3 2013
Firstpage :
368
Lastpage :
375
Abstract :
In this paper, we propose a novel model for finding experts on a given topic using social influence analysis in enterprise social network. In enterprise social networks, employees usually talk about some topics relevant to their tasks. With the integration of social technology in BPM (Business Process Management), more expertise characteristics are reflected by their actions in social networks. Social networks became an important place for sharing expertise. We explore the potential of enterprise social networks, such as Yammer and IBM Connections, as a source of expertise evidence. In this work, we utilized influence analysis approach to find experts in enterprise social network. Generally, not all experts have the habit of sharing their expertise in social networks. So expert finding approaches, such as simply using link analysis, are of limited use. Our approach can address this problem. The experimental results show that the proposed approach can find real experts, not just managers with higher influence. Empirical results have also been presented to demonstrate the effectiveness of the proposed models.
Keywords :
business data processing; social networking (online); BPM; IBM Connections; Yammer; business process management; enterprise social network; influence analysis based expert finding model; social influence analysis; social technology; Algorithm design and analysis; Biological system modeling; Companies; Correlation; Twitter; enterprise social network; expert finding; expertise sharing; influence analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Services Computing (SCC), 2013 IEEE International Conference on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5026-8
Type :
conf
DOI :
10.1109/SCC.2013.72
Filename :
6649717
Link To Document :
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