Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
523313 | Journal of Informetrics | 2009 | 15 Pages |
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 F1F1. F1F1 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Rudy Prabowo, Mike Thelwall,