Mining opinion leaders in big social network

Yi Cheng Chen, Yi Hsiang Chen, Chia Hao Hsu, Hao Jun You, Jianquan Liu, Xin HUANG

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Recently, due to the popularity of Web 2.0, considerable attention has been paid to the opinion leader discovery in social network. By identifying the opinion leaders, companies or governments can manipulate the selling or guiding public opinion, respectively. Additionally, detecting the influential comments is able to understand the source and trend of public opinion formation. However, mining opinion leaders in a huge social network is a challenge task because of the complexity of graph processing and leadership analysis. In this study, a novel algorithm, OLMiner, is proposed to efficiently find the opinion leaders from a huge social network. We propose a clustering method to solve the influence overlapping issue and significantly reduce the computation time by shrinking the size of candidate generation. The experimental results show that the proposed OLMiner can effectively discover the influential opinion leaders in different real social networks with efficiency.

Original languageEnglish
Title of host publicationProceedings - 31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
EditorsTomoya Enokido, Hui-Huang Hsu, Chi-Yi Lin, Makoto Takizawa, Leonard Barolli
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1012-1018
Number of pages7
ISBN (Electronic)9781509060283
DOIs
Publication statusPublished - 5 May 2017
Event31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017 - Taipei, Taiwan, Province of China
Duration: 27 Mar 201729 Mar 2017

Publication series

NameProceedings - International Conference on Advanced Information Networking and Applications, AINA
ISSN (Print)1550-445X

Conference

Conference31st IEEE International Conference on Advanced Information Networking and Applications, AINA 2017
Country/TerritoryTaiwan, Province of China
CityTaipei
Period27/03/1729/03/17

Scopus Subject Areas

  • Engineering(all)

User-Defined Keywords

  • Clustering
  • Opinion leader
  • Semantic analysis
  • Social network

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