Exploring the Sentiment Strength of User Reviews
Existing research efforts in sentiment analysis of online user reviews mainly focus on extracting features (such as quality and price) of prod ucts/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 es timating the sentiment strength of user reviews according to the strength of ad verbs 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 perform ance on a multi-scale evaluation.
opinion mining sentiment analysis sentiment strength text mining
Yao Lu Xiangfei Kong Xiaojun Quan Wenyin Liu Yinlong Xu
Dept. of Computer Sci. and Tech., University of Sci. and Tech. of China, Hefei, China Department of Department of Computer Science, City University of Hong Kong, HKSAR, China Department of Computer Science, City University of Hong Kong, HKSAR, China Joint Research Lab of Exc Dept. of Computer Sci. and Tech., University of Sci. and Tech. of China, Hefei, China Joint Research
国际会议
11th International Conference,WAIM 2010(第十一届网络时代管理国际会议)
九寨沟
英文
471-482
2010-07-14（万方平台首次上网日期，不代表论文的发表时间）