Sentiment analysis: A combined approach

Rudy Prabowo and Mike Thelwall

Journal of Informetrics, 2009, vol. 3, issue 2, 143-157

Abstract: 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 F1. F1 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.

Keywords: Sentiment analysis; Unsupervised learning; Machine learning; Hybrid classification (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (33)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:3:y:2009:i:2:p:143-157

DOI: 10.1016/j.joi.2009.01.003

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