Opinion Expression Mining by Exploiting Keyphrase Extraction

Proceedings of the 5th International Joint Conference on Natural Language Processing, pages 1162–1170, Chiang Mai, Thailand, November 8 – 13, 2011. c⃝2011 AFNLP Opinion Expression Mining by Exploiting Keyphrase Extraction G´abor Berend Department of Informatics, University of Szeged 2. ´Arp´ad t´er, H-6720, Szeged, Hungary berendg@inf.u-szeged.hu Abstract In this paper, we shall introduce a system for extracting the keyphrases for the rea- son of authors’ opinion from product re- views. The datasets for two fairly different product review domains related to movies and mobile phones were constructed semi- automatically based on the pros and cons entered by the authors. The system illus- trates that the classic supervised keyphrase extraction approach – mostly used for sci- entific genre previously – could be adapted for opinion-related keyphrases. Besides adapting the original framework to this special task through defining novel, task- specific features, an efficient way of rep- resenting keyphrase candidates will be demonstrated as well. The paper also pro- vides a comparison of the effectiveness of the standard keyphrase extraction features and that of the system designed for the special task of opinion expression mining. 1 Introduction The amount of community-generated contents on the Web has been steadily growing and most of the end-user contents (e.g. blogs and customer re- views) are likely to deal with the author’s emo- tions and opinions towards some subject. The au- tomatic analysis of such material is useful for both companies and consumers. Companies can eas- ily get an overview of what people think of their products and services and what their most impor- tant strengths and weaknesses are while users can have access to information from the Web before purchasing some product. In this paper we will introduce a system which assigns pro and con keyphrases (free-text anno- tation) to product reviews. When dealing with product reviews, our definition of keyphrases is the set of phrases that make the opinion-holder feel negative or positive towards a given prod- uct, i.e. they should be the reason why the au- thor likes or dislikes the product in question (e.g. cheap price, convenient user interface). Here, we adapted the general keyphrase extraction proce- dure from the scientific publications domain (Wit- ten et al., 1999; Turney, 2003) to the extraction of opinion-reasoning features. However, our task is rather different since we aim at identifying the rea- sons for opinions, instead of keyphrases that rep- resent the content of the whole document. The supervised keyphrase extractor to be in- troduced here was trained on the pros and cons assigned to the reviews by their authors on the epinions.com site. These pros and cons are ill-structured free-text annotations and their length, depth and style are extremely heteroge- neous. In order to have clean gold-standard cor- pora, we manually revised the segmentation and the contents of the pros and cons, and obtained sets of tag-like keyphrases. 2 Related work There have been many studies on opinion mining (Turney, 2002; Pang et al., 2002; Titov and Mc- Donald, 2008; Liu and Seneff, 2009). Our …

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