Deriving marketing intelligence over microblogs

Yung-Ming Li*, Tsung Ying Li

*Corresponding author for this work

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

11 Scopus citations

Abstract

With rapid growing popularity, microblogs have become a great source of consumer opinions. Confronting unique properties and massive volume of posts on microblogs, this paper proposes a summarization framework that provides compact numeric summarization for microblogs opinions. The proposed framework is designed to cope with four major tasks: 1) topics detection, 2) sentiment classification, 3) credibility assessment and 4) score aggregation. The experiment is held on twitter, the largest microblog platform, for proving the efficiency and correctness of the framework. We found the consideration of user credibility and opinion quality is essential for aggregating microblog opinions.

Original languageEnglish
Title of host publicationProceedings of the 44th Annual Hawaii International Conference on System Sciences, HICSS-44 2010
DOIs
StatePublished - 28 Mar 2011
Event44th Hawaii International Conference on System Sciences, HICSS-44 2010 - Koloa, Kauai, HI, United States
Duration: 4 Jan 20117 Jan 2011

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605

Conference

Conference44th Hawaii International Conference on System Sciences, HICSS-44 2010
CountryUnited States
CityKoloa, Kauai, HI
Period4/01/117/01/11

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