Mining Opinions in Comparative Sentences

Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008), pages 241–248 Manchester, August 2008 Mining Opinions in Comparative Sentences Murthy Ganapathibhotla Department of Computer Science University of Illinois at Chicago 851 South Morgan Street Chicago, IL 60607-7053 sganapat@cs.uic.edu Bing Liu Department of Computer Science University of Illinois at Chicago 851 South Morgan Street Chicago, IL 60607-7053 liub@cs.uic.edu Abstract 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 compari- son 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. Clear- ly, “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 pa- per studies this problem, and proposes a technique to solve the problem. Our ex- periments using comparative sentences from product reviews and forum posts show that the approach is effective. 1 Introduction In the past few years, there was a growing inter- est in mining opinions in the user-generated con- tent (UGC) on the Web, e.g., customer reviews, forum posts, and blogs. One major focus is sen- timent classification and opinion mining (e.g., Pang et al 2002; Turney 2002; Hu and Liu 2004; Wilson et al 2004; Kim and Hovy 2004; Popescu and Etzioni 2005) © 2008. Licensed under the Creative Commons Attri- bution-Noncommercial-Share Alike 3.0 Unported license (http://creativecommons.org/licenses/by-nc- sa/3.0/). Some rights reserved. However, these studies mainly center on direct opinions or sentiments expressed on entities. Lit- tle study has been done on comparisons, which represent another type of opinion-bearing text. Comparisons are related to but are also quite dif- ferent from direct opinions. For example, a typi- cal direct opinion sentence is “the picture quality of Camera X is great”, while a typical compara- tive sentence is “the picture quality of Camera X is better than that of Camera Y.” We can see that comparisons use different language constructs from direct opinions. A comparison typically expresses a comparative opinion on two or more entities with regard to their shared features or attributes, e.g., “picture quality”. Although direct opinions are most common in UGC, comparisons are also widely used (about 10% of the sen- tences), especially in forum discussions where users often ask questions such as “X vs. Y” (X and Y are competing products). Discussions are then centered on comparisons. Jindal and Liu (2006) proposed a technique to identify comparative sentences from reviews and forum posts, and to extract entities, comparative words, and entity features that are being com- pared. For example, in the sentence, “Camera X has longer battery life than Camera Y”, the technique extracts “Camera X” …

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