A constrained multi-view clustering approach to influence role detection

Chengyao Chen, Dehong Gao, Wenjie Li, Yuexian Hou

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review


Twitter has provided people with an effective way to communicate and interact with each other. It is an undisputable fact that people’s influence plays an important role in disseminating information over the Twitter social network. Although a number of research work on finding influential users have been reported in the literature, they never really seek to distinguish and analyze different influence roles, which are of great value for various marketing purposes. In this chapter, we move a step forward to further detect five recognized influence roles of Twitter users with regard to a particular topic. By exploring three views of features related to topic, sentiment and popularity respectively, we propose a novel constrained multi-view influence role clustering approach to group potential influential Twitter users into five categories. Experimental results demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationSocial Media Content Analysis
Subtitle of host publicationNatural Language Processing and Beyond
PublisherWorld Scientific Publishing Co. Pte. Ltd.
Number of pages16
ISBN (Electronic)9789813223615
ISBN (Print)9789813223608
Publication statusPublished - 1 Jan 2017

ASJC Scopus subject areas

  • Computer Science(all)


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