NDLI: Simple linguistic processing effect on multi-label emotion classification

Content Provider	IEEE Xplore Digital Library
Author	Ye Wu Ren, F.
Copyright Year	2009
Description	Author affiliation: School of Computer, Beijing University of Posts and Telecommunications, Beijing, China (Ye Wu; Ren, F.)
Abstract	Emotion plays a significant role in human communications in our daily life. With progress in human-machine interface technology, recent research has placed more emphasis on the recognition of emotion reaction. Comparing to some other ideal experimental settings, blog posts online would be respond more to real-world events. And a huge resource of text-based emotion can be found from the World Wide Web nowadays. This paper reports a study to investigate the effectiveness of using SVM (Support Vector Machine) on linguistic features considering emotion keywords and negative words, and classify a collection of blog posts sentences tagged by one or more labels finally. Our results show that individual emotions can be clearly separated by the proposed approach. To the multi-label classification of emotion, it also obtained a higher accuracy rate than the baseline unigram approach using SVM.
Starting Page	1
Ending Page	5
File Size	215363
Page Count	5
File Format	PDF
ISBN	9781424445387
DOI	10.1109/NLPKE.2009.5313832
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Emotion recognition Humans Emotion classification Telecommunication computing SVM Speech synthesis multi-label Support vector machines Information services Support vector machine classification Internet Man machine systems Web sites
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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