Finding Appropriate Turning Point for Text Sentiment Polarity

Authors:
Haipeng Wang;Lin Shang;Xinyu Dai;Cunyan Yin
Affiliations:
State Key Laboratory for Novel Software Technology, Nanjing University, Department of Computer Science and Technology, Nanjing University,;State Key Laboratory for Novel Software Technology, Nanjing University, Department of Computer Science and Technology, Nanjing University,;State Key Laboratory for Novel Software Technology, Nanjing University, Department of Computer Science and Technology, Nanjing University,;State Key Laboratory for Novel Software Technology, Nanjing University, Department of Computer Science and Technology, Nanjing University,
Venue:
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Year:
2009

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Abstract

Sentiment analysis has attracted more and more attention in recent years. Neural network can be trained to calculate the sentiment orientation value of the text. After getting the value, a turning point is used to identify the text polarity. The midpoint 0.5 is often used as the turning point, however, we show in this paper that the midpoint is not always good for getting the highest classification precision. In the paper, three methods are proposed to find the appropriate turning point. We prepare the book review from Amazon.com and experiment our three methods. Neural Network classifier is employed in experiments and the results show the better precision compared with midpoint method.