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Issue No.05 - Sept.-Oct. (2012 vol.27)
pp: 44-50
Christopher C. Yang , Drexel University
Xuning Tang , Drexel University
ABSTRACT
A method of identifying influential users in an online healthcare community incorporates users' message similarity and response immediacy.
INDEX TERMS
Social network services, Algorithm design and analysis, Communities, Online services, Internet, Diseases, Medical services, social networking, social medial analytics, social computing, Web 2.0, health informatics, social influence, UserRank, PageRank, content analysis, link analysis
CITATION
Christopher C. Yang, Xuning Tang, "Estimating User Influence in the MedHelp Social Network", IEEE Intelligent Systems, vol.27, no. 5, pp. 44-50, Sept.-Oct. 2012, doi:10.1109/MIS.2010.113
REFERENCES
1. K. Chuang and C.C. Yang, "Social Support in Online Healthcare Social Networking," Proc. 2010 iConference, 2010, pp. 43–47; www.ideals.illinois.edu/bitstream/handle/ 2142/14927chuang.pdf.
2. K. Chuang and C.C. Yang, "Helping You to Help Me: Exploring Supportive Interaction in Online Health Community," Proc. Am. Soc. Information Science and Technology (ASIS&T 10), American Society for Information Science, vol. 47, no. 9, pp. 1–10.
3. J. Zhang, M. Ackerman, and L. Adamic, "Expertise Networks in Online Communities: Structure and Algorithms," Proc. 16th Int'l Conf. World Wide Web, ACM, 2007, pp. 221–230.
4. R. Fagin, R. Kumar, and D. Sivakumar, "Comparing Top-k Lists," SIAM J. Discrete Mathematics, vol. 17, no. 1, 2003, pp. 134–160.
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