Exploring the sentiment strength of user reviews

Authors:
Yao Lu;Xiangfei Kong;Xiaojun Quan;Wenyin Liu;Yinlong Xu
Affiliations:
Dept. of Computer Sci. and Tech., University of Sci. and Tech. of China, Hefei, China and Department of Computer Science, City University of Hong Kong, HKSAR, China;Department of Computer Science, City University of Hong Kong, HKSAR, China;Department of Computer Science, City University of Hong Kong, HKSAR, China;Department of Computer Science, City University of Hong Kong, HKSAR, China and CityU-USTC Advanced Research Institute, Suzhou, China;Dept. of Computer Sci. and Tech., University of Sci. and Tech. of China, Hefei, China and CityU-USTC Advanced Research Institute, Suzhou, China
Venue:
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Year:
2010

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Abstract

Existing research efforts in sentiment analysis of online user reviews mainly focus on extracting features (such as quality and price) of products/ services and classifying users' sentiments into semantic orientations (such as positive, negative or neutral). However, few of them take the strength of user sentiments into consideration, which is particularly important in measuring the overall quality of products/services. Intuitively, different reviews for the same feature should have quite different sentiment strength, even though they may express the same polarity of sentiment. This paper presents an approach to estimating the sentiment strength of user reviews according to the strength of adverbs and adjectives expressed by users in their opinion phrases. Experimental result on a hotel review dataset in Chinese shows that the proposed approach is effective in the task of sentiment classification and achieves a good performance on a multi-scale evaluation.