This paper studies sentiment analysis from the user-generated content on the Web. In particular, it focuses on mining opinions from comparative sentences, i.e., to determine which entities in a comparison are preferred by its author. A typical comparative sentence compares two or more entities. For example, the sentence, "the picture quality of Camera X is better than that of Camera Y", compares two entities "Camera X" and "Camera Y" with regard to their picture quality. Clearly, "Camera X" is the preferred entity. Existing research has studied the problem of extracting some key elements in a comparative sentence. However, there is still no study of mining opinions from comparative sentences, i.e., identifying preferred entities of the author. This paper studies this problem, and proposes a technique to solve the problem. Our experiments using comparative sentences from product reviews and forum posts show that the approach is effective.
Ganapathibhotla and Liu REF focused on determining which entities in comparison are preferred by users.
Mining Opinions in Comparative Sentences
International Conference On Computational Linguistics
Computer Science