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dc.contributor.authorShahheidari, S.
dc.contributor.authorDong, Hai
dc.contributor.authorBin Daud, M.N.R.
dc.contributor.editorLeonard Barolli, Fatos Xhafa, Hsing-Chung Chen, Antonio F. Skarmeta Gómez, and Farookh Hussain
dc.date.accessioned2017-01-30T13:42:31Z
dc.date.available2017-01-30T13:42:31Z
dc.date.created2013-09-30T20:00:36Z
dc.date.issued2013
dc.identifier.citationShahheidari, Saeideh and Dong, Hai and Bin Daud, M.N.R. 2013. Twitter Sentiment Mining: A Multi Domain Analysis, in Barolli, L. and Xhafa, F. and Chen, H.C. and Gómez-Skarmeta, A.F. and Hussain, F. (ed), Seventh International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), Jul 3-5 2013, pp. 144-149. Asia University, Taichung, Taiwan: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/34303
dc.identifier.doi10.1109/CISIS.2013.31
dc.description.abstract

Microblogging such as Twitter provides a rich source of information about products, personalities, and trends, etc. We proposed a simple methodology for analyzing sentiment of users in Twitter. First, we automatically collected Twitter corpus in positive and negative tweets. Second, we built a simple sentiment classifier by utilizing the Naive Bayes model to determine the positive and negative sentiment of a tweet. Third, we tested the classifier against a collection of users’ opinions from five interesting domains of Twitter, i.e., news, finance, job, movies, and sport. The experimental results show that it is feasible to use Twitter corpus alone to classify new tweet for a certain domain applications.

dc.publisherCPS
dc.subjectsocial media
dc.subjecttext mining
dc.subjectclassifier
dc.subjectOpinion mining
dc.subjectsentiment analysis
dc.titleTwitter Sentiment Mining: A Multi Domain Analysis
dc.typeConference Paper
dcterms.source.startPage144
dcterms.source.endPage149
dcterms.source.title2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems
dcterms.source.series2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems
dcterms.source.isbn978-0-7695-4992-7
dcterms.source.conferenceCISIS 2013
dcterms.source.conference-start-dateJul 3 2013
dcterms.source.conferencelocationAsia University, Taichung, Taiwan
dcterms.source.placeJapan
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Copyright © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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curtin.accessStatusOpen access


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