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IOS Press Social Influence Analysis in Microblogging
BibTeX
@MISC{Based_iospress,
author = {Platforms A Topic-sensitive Based and Amparo E. Cano A and Suvodeep Mazumdar A and Fabio Ciravegna A},
title = {IOS Press Social Influence Analysis in Microblogging},
year = {}
}
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Abstract
Abstract. The use of Social Media, particularly microblogging platforms such as Twitter, has proven to be an effective channel for pro-moting 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 rele-vance 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 PageR-ank algorithm for analysing users ’ topical and entity influence based on the topical/entity relevance of a retweet relation. Experi-mental 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.
Keyphrases
io press social influence analysis social medium data approach outperforms large-scale network top influential user mention relation social medium entity influence pager-ank algorithm experi-mental result topic-sensitive pagerank topical entity relevance retweet relation effective channel retweet subgraph topical rele-vance influential user pro-moting idea semantic profile twitter graph recent research topical query need visualisation platform public opinion
