Cano, A.E., Mazumdar, S. and Ciravegna, F. orcid.org/0000-0001-5817-4810 (2014) Social influence analysis in microblogging platforms - A topic-sensitive based approach. Semantic Web, 5 (5). pp. 357-372. ISSN 1570-0844
Abstract
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 user 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 IOS Press. This is an author-produced version of a paper subsequently published in Semantic Web. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | social awareness streams; microblogging; social influence; semantic profiles |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Mar 2020 13:51 |
Last Modified: | 06 Mar 2020 02:40 |
Status: | Published |
Publisher: | IOS Press |
Refereed: | Yes |
Identification Number: | 10.3233/SW-130108 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158112 |