Hierarchical classification in text mining for sentiment analysis of online news
Jinyan Li1; Simon Fong1; Yan Zhuang1; Richard Khoury2
2016-09-01
Source PublicationSoft Computing
ISSN1432-7643
Volume20Issue:9Pages:3411-3420
Abstract

Sentiment analysis in text mining is a challenging task. Sentiment is subtly reflected by the tone and affective content of a writer’s words. Conventional text mining techniques, which are based on keyword frequencies, usually run short of accurately detecting such subjective information implied in the text. In this paper, we evaluate several popular classification algorithms, along with three filtering schemes. The filtering schemes progressively shrink the original dataset with respect to the contextual polarity and frequent terms of a document. We call this approach “hierarchical classification”. The effects of the approach in different combination of classification algorithms and filtering schemes are discussed over three sets of controversial online news articles where binary and multi-class classifications are applied. Meanwhile we use two methods to test this hierarchical classification model, and also have a comparison of the two methods.

KeywordClassification Sentiment Analysis Text Mining
DOIhttps://doi.org/10.1007/s00500-015-1812-4
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000381998000008
PublisherSPRINGER, 233 SPRING ST, NEW YORK, NY 10013 USA
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Citation statistics
Cited Times [WOS]:21   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorJinyan Li; Simon Fong; Yan Zhuang; Richard Khoury
Affiliation1.Department of Computer and Information Science, University of Macau, Taipa, Macau SAR
2.Department of Software Engineering, Lakehead University, Thunder Bay, Canada
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Jinyan Li,Simon Fong,Yan Zhuang,et al. Hierarchical classification in text mining for sentiment analysis of online news[J]. Soft Computing,2016,20(9):3411-3420.
APA Jinyan Li,Simon Fong,Yan Zhuang,&Richard Khoury.(2016).Hierarchical classification in text mining for sentiment analysis of online news.Soft Computing,20(9),3411-3420.
MLA Jinyan Li,et al."Hierarchical classification in text mining for sentiment analysis of online news".Soft Computing 20.9(2016):3411-3420.
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