Aspect Ranking: Identifying Important Product Aspects from Online Consumer Reviews

Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pages 1496–1505, Portland, Oregon, June 19-24, 2011. c⃝2011 Association for Computational Linguistics Aspect Ranking: Identifying Important Product Aspects from Online Consumer Reviews Jianxing Yu, Zheng-Jun Zha, Meng Wang, Tat-Seng Chua School of Computing National University of Singapore {jianxing, zhazj, wangm, chuats}@comp.nus.edu.sg Abstract In this paper, we dedicate to the topic of aspect ranking, which aims to automatically identify important product aspects from online con- sumer reviews. The important aspects are identified according to two observations: (a) the important aspects of a product are usually commented by a large number of consumers; and (b) consumers’ opinions on the important aspects greatly influence their overall opin- ions on the product. In particular, given con- sumer reviews of a product, we first identify the product aspects by a shallow dependency parser and determine consumers’ opinions on these aspects via a sentiment classifier. We then develop an aspect ranking algorithm to identify the important aspects by simultane- ously considering the aspect frequency and the influence of consumers’ opinions given to each aspect on their overall opinions. The ex- perimental results on 11 popular products in four domains demonstrate the effectiveness of our approach. We further apply the aspect ranking results to the application of document- level sentiment classification, and improve the performance significantly. 1 Introduction The rapidly expanding e-commerce has facilitated consumers to purchase products online. More than $156 million online product retail sales have been done in the US market during 2009 (Forrester Re- search, 2009). Most retail Web sites encourage con- sumers to write reviews to express their opinions on various aspects of the products. This gives rise to Figure 1: Sample reviews on iPhone 3GS product huge collections of consumer reviews on the Web. These reviews have become an important resource for both consumers and firms. Consumers com- monly seek quality information from online con- sumer reviews prior to purchasing a product, while many firms use online consumer reviews as an im- portant resource in their product development, mar- keting, and consumer relationship management. As illustrated in Figure 1, most online reviews express consumers’ overall opinion ratings on the product, and their opinions on multiple aspects of the prod- uct. While a product may have hundreds of aspects, we argue that some aspects are more important than the others and have greater influence on consumers’ purchase decisions as well as firms’ product devel- opment strategies. Take iPhone 3GS as an exam- ple, some aspects like “battery” and “speed,” are more important than the others like “moisture sen- sor.” Generally, identifying the important product aspects will benefit both consumers and firms. Con- sumers can conveniently make wise purchase deci- sion by paying attentions on the important aspects, while firms can focus on improving the quality of 1496 these aspects and thus enhance the product reputa- tion effectively. However, it is impractical for people to identify the important aspects from the numerous reviews manually. Thus, it becomes a compelling need to …

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