Deriving market intelligence from microblogs

Yung-Ming Li*, Tsung Ying Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

96 Scopus citations


Given their rapidly growing popularity, microblogs have become great sources of consumer opinions. However, in the face of unique properties and the massive volume of posts on microblogs, this paper proposes a framework that provides a compact numeric summarization of opinions on such platforms. The proposed framework is designed to cope with the following tasks: trendy topics detection, opinion classification, credibility assessment, and numeric summarization. An experiment is carried out on Twitter, the largest microblog website, to prove the effectiveness of the proposed framework. We find that the consideration of user credibility and opinion subjectivity is essential for aggregating microblog opinions. The proposed mechanism can effectively discover market intelligence (MI) for supporting decision-makers.

Original languageEnglish
Pages (from-to)206-217
Number of pages12
JournalDecision Support Systems
Issue number1
StatePublished - 1 Apr 2013


  • Credibility assessment
  • Market trends
  • Microblog
  • Opinion classification
  • Sentiment classification
  • Social media

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