Improving sentiment analysis with Part-of-Speech weighting

Sentiment analysis is concerned with classifying the opinions in a piece of text. We present a term weighting scheme which takes into account part-of-speech categories to improve machine learning-based classification of sentiment in product reviews. We experimentally find optimal strengths for each...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 3; pp. 1592 - 1597
Main Authors Nicholls, C., Fei Song
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Cybernetics
Electronic mail
Entropy
Feature Selection
Feature Weighting
Information analysis
Information science
Internet
Labeling
Machine learning
Part-of-Speech Tagging
Sentiment Analysis
Tagging
Text categorization
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Summary:Sentiment analysis is concerned with classifying the opinions in a piece of text. We present a term weighting scheme which takes into account part-of-speech categories to improve machine learning-based classification of sentiment in product reviews. We experimentally find optimal strengths for each part-of-speech category and show that using this weighting method improves overall sentiment classification.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212278