Krunoslav Zubrinic, Tomo Sjekavica, Mario Milicevic, Ines Obradovic
In this paper we analyze reviews written by customers of an online shop, by employing opinion polarity classification on document level using five machine learning algorithms: Na¨ive Bayes, Support Vector Machine, Neural networks, C4.5 algorithm and classifier based on maximum entropy. We achieved the best results using Support Vector Machine algorithm (accuracy=0.845) and maximum entropy classifier (accuracy=0.84). Although those results are not as good as results that can be achieved in topic-based categorization, compared to similar researches in opinion polarity classification, they indicate a relatively good predictive performance of classical machine learning algorithms.
opinion polarity classification, sentiment analysis, natural language processing
Cite this paper
Krunoslav Zubrinic, Tomo Sjekavica, Mario Milicevic, Ines Obradovic. (2018) A Comparison of Machine Learning Algorithms in Opinion Polarity Classification of Customer Reviews. International Journal of Computers, 3, 159-163