UM  > 科技學院  > 電腦及資訊科學系
Mining Twitterspace for Information: Classifying Sentiments Programmatically using Java
Jinan Fiaidhi1; Osama Mohammed2; Sabah Mohammed1; Simon Fong3; Tai hoon Kim4
2012-12-31
Conference NameSeventh International Conference on Digital Information Management (ICDIM 2012)
Source Publication7th International Conference on Digital Information Management, ICDIM 2012
Pages303-308
Conference Date22-24 Aug. 2012
Conference PlaceMacau, China
PublisherIEEE
Abstract

People increasingly use Twitter to share advice, opinions, news, moods, concerns, facts, rumors, and everything else imaginable. Much of that data is public and available for mining. However, classifying automatically the sentiment of the Twitter messages into either positive or negative with respect to a query term represents a new research challenge. Variety of approaches that use natural language and statistical techniques failed to report high accuracy of tweets classification due to the nature of these tweets containing large number of abbreviations, emoticons and ill structured grammar. In this article we are presenting a programming approach that uses the Weka data mining APIs to classify tweets. Using this programming approach we can experiment on how to train the classifiers and determine which one is more effective than the others. In our experiments, the K* classifier is found to report a high degree of accuracy in tweets classification. 

KeywordClassification Algorithms Data Mining Sentiment Analysis Twitter
DOIhttps://doi.org/10.1109/ICDIM.2012.6360089
URLView the original
Indexed By其他
Language英语
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer Science, Lakehead University, Thunder Bay
2.Department of Software Engineering. Lakehead University, Thunder Bay,
3.Faculty of Science and Technology University of Macau, Macau, China
4.Department of Computer Engineering, Glocal Campus, Konkuk University, Korea
Recommended Citation
GB/T 7714
Jinan Fiaidhi,Osama Mohammed,Sabah Mohammed,et al. Mining Twitterspace for Information: Classifying Sentiments Programmatically using Java[C]:IEEE,2012:303-308.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jinan Fiaidhi]'s Articles
[Osama Mohammed]'s Articles
[Sabah Mohammed]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jinan Fiaidhi]'s Articles
[Osama Mohammed]'s Articles
[Sabah Mohammed]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jinan Fiaidhi]'s Articles
[Osama Mohammed]'s Articles
[Sabah Mohammed]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.