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Social influence analysis in microblogging platforms - a topic-sensitive based approach

Cano Basave, A. E.; Mazumdar, S. and Ciravegna, F. (2014). Social influence analysis in microblogging platforms - a topic-sensitive based approach. Semantic Web, 5(5) pp. 357–403.

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The use of Social Media, particularly microblogging platforms such as Twitter, has proven to be an effective channel for promoting ideas to online audiences. In a world where information can bias public opinion it is essential to analyse the propagation and influence of information in large-scale networks. Recent research studying social media data to rank users by topical relevance have largely focused on the “retweet", “following" and “mention" relations. In this paper we propose the use of semantic profiles for deriving influential users based on the retweet subgraph of the Twitter graph. We introduce a variation of the PageRank algorithm for analysing users’ topical and entity influence based on the topical/entity relevance of a retweet relation. Experimental results show that our approach outperforms related algorithms including HITS, InDegree and Topic-Sensitive PageRank. We also introduce VisInfluence, a visualisation platform for presenting top influential users based on a topical query need.

Item Type: Journal Item
Copyright Holders: 2011 IOS Press and the Authors
ISSN: 2210-4968
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetGrant 175203CONACyT
Samulet (Strategic Affordable Manufacturing in the UK through Leading Environmental Technologies)Not SetTSB and Physical Sciences Research Council
Keywords: social awareness streams; microblogging; social influence; semantic profiles
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 41412
Depositing User: Amparo Cano Basave
Date Deposited: 26 Nov 2014 12:30
Last Modified: 09 Dec 2018 23:21
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