Finding influential users of web event in social media

Abstract

Users of social media have different influences on the evolution of a Web event. Finding influential users could benefit such information services as recommendation and market analysis. However, most of the existing methods are only based on social networks of users or user behaviors while the role of the contents contributed by users in social media is ignored. In fact, a Web event evolves with both user behaviors and the contents. This paper proposes an approach to find influential users by extracting user behavior network and association network of words within the contents and then uses PageRank algorithm and HITS algorithm to calculate the influence of users on the integration of two networks. The proposed approach is effective on several real-world datasets.

Publication DOI: https://doi.org/10.1002/cpe.5029
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: This is the peer reviewed version of the following article: Ma Q, Luo X, Zhuge H. Finding influential users of web event in social media. Concurrency Computat Pract Exper. 2018;e5029., which has been published in final form at https://doi.org/10.1002/cpe.5029.  This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords: influential user,social media,social network,Web event,Software,Theoretical Computer Science,Computer Science Applications,Computer Networks and Communications,Computational Theory and Mathematics
Publication ISSN: 1532-0634
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://onlinel ... 0.1002/cpe.5029 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-02-10
Published Online Date: 2018-10-21
Accepted Date: 2018-09-14
Authors: Ma, Qichen
Luo, Xiangfeng
Zhuge, Hai (ORCID Profile 0000-0001-8250-6408)

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