Journal
DECISION SUPPORT SYSTEMS
Volume 55, Issue 1, Pages 206-217Publisher
ELSEVIER
DOI: 10.1016/j.dss.2013.01.023
Keywords
Social media; Microblog; Market trends; Sentiment classification; Credibility assessment; Opinion classification
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Funding
- National Science Council of Taiwan (Republic of China) [NSC 99-2410-H-009-035-MY2]
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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. (C) 2013 Elsevier B.V. All rights reserved.
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