文章基本信息

标题：Sentiment Classification of Portuguese News Headlines
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作者：António Paulo Santos ; Carlos Ramos ; Nuno C. Marques 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：9
页码：9-18
DOI：10.14257/ijseia.2015.9.9.02
出版社：SERSC
摘要：This paper addresses the problem of classifying news headlines into sentiment categories. Using a supervised approach, we train a classifier for classify ing each news headline as positive, negative, or neutral. A news headline is considered positive if it is associated with good things, negative if it is associated with bad things, and neutral in the remaining cases. The experiments show an accuracy that ranges from 59.00% to 63.50% when syntactic features (argument1-verb-argument2 relations) are combined with other features. The accuracy ranges from 57.50% to 62.5% when these relations are not used.
关键词：sentiment classification; news headlines