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Identifying opinion leaders from online comments

  • Yi Chen
  • , Xiaolong Wang
  • , Buzhou Tang*
  • , Ruifeng Xu
  • , Bo Yuan
  • , Xin Xiang
  • , Junzhao Bu
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Online comments are ubiquitous in social media such as micro-blogs, forums and blogs. They provide opinions of reviewers that are useful for understanding social media. Identifying opinion leaders from all reviewers is one of the most important tasks to analysis online comments. Most existing methods to identify opinion leaders only consider positive opinions. Few studies investigate the effect of negative opinions on opinion leader identification. In this paper, we propose a novel method to identify opinion leaders from online comments based on both positive and negative opinions. In this method, we first construct a signed network from online comments, and then design a new model based on PageTrust, called TrustRank, to identify opinion leaders from the signed network. Experimental results on the online comments of a real forum show that the proposed method is competitive with other related state-of-the-art methods.

Original languageEnglish
Title of host publicationSocial Media Processing - 3rd National Conference, SMP 2014, Proceedings
EditorsJie Tang, Ting Liu, Heyan Huang, Hua-Ping Zhang
PublisherSpringer Verlag
Pages231-239
Number of pages9
ISBN (Electronic)9783662455579
DOIs
StatePublished - 2014
Externally publishedYes
Event3rd National Conference on Social Media Processing, SMP 2014 - Beijing, China
Duration: 1 Nov 20142 Nov 2014

Publication series

NameCommunications in Computer and Information Science
Volume489
ISSN (Print)1865-0929

Conference

Conference3rd National Conference on Social Media Processing, SMP 2014
Country/TerritoryChina
CityBeijing
Period1/11/142/11/14

Keywords

  • Online comments
  • Opinion leader
  • PageRank
  • Signed networks

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