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Sentiment analysis: A combined approach

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  • Prabowo, Rudy
  • Thelwall, Mike

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.

Suggested Citation

  • Prabowo, Rudy & Thelwall, Mike, 2009. "Sentiment analysis: A combined approach," Journal of Informetrics, Elsevier, vol. 3(2), pages 143-157.
    • Handle: RePEc:eee:infome:v:3:y:2009:i:2:p:143-157
    DOI: 10.1016/j.joi.2009.01.003
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    References listed on IDEAS

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