作者
Cagatay Catal, Mehmet Nangir
发表日期
2017/1/1
期刊
Applied Soft Computing
卷号
50
页码范围
135-141
出版商
Elsevier
简介
With the widespread usage of social networks, forums and blogs, customer reviews emerged as a critical factor for the customers’ purchase decisions. Since the beginning of 2000s, researchers started to focus on these reviews to automatically categorize them into polarity levels such as positive, negative, and neutral. This research problem is known as sentiment classification. The objective of this study is to investigate the potential benefit of multiple classifier systems concept on Turkish sentiment classification problem and propose a novel classification technique. Vote algorithm has been used in conjunction with three classifiers, namely Naive Bayes, Support Vector Machine (SVM), and Bagging. Parameters of the SVM have been optimized when it was used as an individual classifier. Experimental results showed that multiple classifier systems increase the performance of individual classifiers on Turkish …
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