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2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2014)
China
Aug. 17, 2014 to Aug. 20, 2014
ISBN: 978-1-4799-5877-1
pp: 460-463
Wayne Xin Zhao , School of Information, Renmin University of China, Beijing, China
Jing Liu , Microsoft Research, Beijing, China
Yulan He , School of Engineering and Applied Science, Aston University, UK
Chin-Yew Lin , Microsoft Research, Beijing, China
Ji-Rong Wen , School of Information, Renmin University of China, Beijing, China
ABSTRACT
Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally “Sina microblogging”). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the “audience” in their expertise domains.
INDEX TERMS
Correlation, Media, Social network services, Conferences, Entertainment industry, Business, Educational institutions
CITATION

W. X. Zhao, J. Liu, Y. He, C. Lin and J. Wen, "A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs," 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), China, 2014, pp. 460-463.
doi:10.1109/ASONAM.2014.6921626
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