文章基本信息

标题：Web Application for Sentiment Analysis Using Supervised Machine Learning
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作者：Bryan Nii Lartey Laryea ; Chi-Hwan Choi ; In-Sun Jung 等
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2015
卷号：9
期号：1
页码：191-200
DOI：10.14257/ijseia.2015.9.1.17
出版社：SERSC
摘要：Sentiment analysis is now in focus of companies to extract information from customers' reviews. Usually the analysis classification is positive, negative and neutral. In this research we focus on the reviews for electronic products. The demographic and technical expertise level of consumers and reviewers are diverse hence there is difference in the way they review a product. Some review contains technical solutions, improvised ways of tackling problems, frustrations, joy etc. This differences in review calls for a wider classification scheme to contain these differences. We thereby introduced a five classification scheme namely positive, negative, advice, no sentiment and neutral at the sentence. We crawled data from amazon.com and used open source natural language processing tools to get the sentiment out of the review.
关键词：Sentiment analysis; Machine learning; Na.ve Bayes; Support vector machine ; (SVM); Corpus; Ling Pipe Classifier