A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

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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.

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Details

Publication date2014
Publication titleProceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining : ASONAM 2014
EditorsXindong Wu, Martin Ester, Guandong Xu
Place of PublicationPiscataway, NJ (US)
PublisherIEEE
Pages460-463
Number of pages4
ISBN (Print)978-1-4799-5877-1, 978-1-4799-5876-4
Original languageEnglish
Event2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining - Beijing, China

Conference

Conference2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining
Abbreviated titleASONAM 2014
CountryChina
CityBeijing
Period17/08/1420/08/14

Bibliographic note

Funding: EPSRC grant EP/L010690/1

    Keywords

  • expertise, microblog, social media influence

DOI

Employable Graduates; Exploitable Research

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