Sentiment analysis: A combined approach
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 F 1 . F1 F 1 is a measure that takes both the precision and recall of a classifiers 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.
sentiment analysis machine learning hybrid classification unsupervised learning