期刊
JOURNAL OF INFORMETRICS
卷 3, 期 2, 页码 143-157出版社
ELSEVIER
DOI: 10.1016/j.joi.2009.01.003
关键词
Sentiment analysis; Unsupervised learning; Machine learning; Hybrid classification
Sentiment analysis is an important current research area. This paper combines rule-based classification, supervised learning and machine learning into a new combined method. This method is tested on movie reviews, product reviews and MySpace comments. The results show that a hybrid classification can improve the classification effectiveness in terms of micro- and macro-averaged F-1. F-1 is a measure that takes both the precision and recall of a classifier's effectiveness into account. In addition, we propose a semi-automatic, complementary approach in which each classifier can contribute to other classifiers to achieve a good level of effectiveness. (C) 2009 Elsevier Ltd. All rights reserved.
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