Finding interesting posts in Twitter based on retweet graph analysis

Min Chul Yang, Jung Tae Lee, Seung Wook Lee, Hae Chang Rim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Millions of posts are being generated in real-time by users in social networking services, such as Twitter. However, a considerable number of those posts are mundane posts that are of interest to the authors and possibly their friends only. This paper investigates the problem of automatically discovering valuable posts that may be of potential interest to a wider audience. Specifically, we model the structure of Twitter as a graph consisting of users and posts as nodes and retweet relations between the nodes as edges. We propose a variant of the HITS algorithm for producing a static ranking of posts. Experimental results on real world data demonstrate that our method can achieve better performance than several baseline methods.

Original languageEnglish
Title of host publicationSIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages1073-1074
Number of pages2
DOIs
Publication statusPublished - 2012
Event35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012 - Portland, OR, United States
Duration: 2012 Aug 122012 Aug 16

Publication series

NameSIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012
Country/TerritoryUnited States
CityPortland, OR
Period12/8/1212/8/16

Keywords

  • Twitter
  • hits
  • social network
  • tweet ranking

ASJC Scopus subject areas

  • Information Systems

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