Hierarchical organization of consumer reviews for products and its applications

HIERARCHICAL ORGANIZATION OF CONSUMER REVIEWS FOR PRODUCTS AND ITS APPLICATIONS YU JIANXING A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY SCHOOL OF COMPUTING NATIONAL UNIVERSITY OF SINGAPORE 2012 c ⃝2012 YU JIANXING Acknowledgements I would like to express my gratitude to all those who contributed and extended their valuable assistance to help me prepare and complete this thesis. My deepest gratitude goes first and foremost to my advisor, Prof. Chua Tat-Seng, who led me through the four years of Ph.D study and research. His perpetual enthusiasm, valuable insight, and unconventional vision in research had consistently motivated me to explore my work in the topic of sentiment analysis. I am deeply grateful for his thoughtful, patient, and kind guidance during the graduate training. To me, Prof. Chua is not only an academic advisor, but also a role model and a lifetime mentor. His valuable advice adds considerably to my graduate experience, and his influence has been undoubtedly beyond the research aspect of my life. Besides my advisor, I wish to express my sincerest gratitude to my thesis committee, including Prof. Ng Hwee Tou, Prof. Tan Chew Lim and external examiners, for their critical readings and constructive criticisms, which make the thesis as sound as possible. I greatly benefit from their encouragements, brilliant ideas and high standard questions. It is an incredible honor to be examined by such knowledgeable people. Very special thanks go to Dr. Zha Zheng-Jun, for his instructive guidance, insightful criticism and inspiring questions. Dr. Zha had spent much time discussing the research topics with me and helped me go through many obstacles. Also, I would like to thank all my labmates in Lab for Media Search (LMS) for their stimulating discussions and enlightening suggestions on my work. I extend my thanks to Loo Line Fong, for her always kind help in coordinating all administrative stuffs in my four years in the school of computing. Moreover, I must acknowledge National University of Singapore and School of Computing for their technical and financial support. Last but not least, my gratitude would go to my family and my friends, especially Guo iii Jiayan, for their consistent supports and sincere helps throughout my life. Without them, this thesis would not be possible. My gratitude towards them is truly beyond words. iv Table of Contents Acknowledgements iii Abstract ix List of Figures xii List of Tables xv Chapter Introduction 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Guide to This thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chapter Literature Review 11 2.1 Overview of Research Topics in Sentiment Analysis . . . . . . . . . . . 11 2.2 Generation of Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 Product Aspect Identification . . . . . . . . . . . . . . . . . . . 15 2.2.2 Sentiment Classification on Product Aspects . . . . . . . . . . 16 2.2.3 Acquisition of Parent-child Relations . . . . . . . . . . . . . . 17 v 2.3 2.4 2.2.3.1 Pattern-based Approach . . . . . . . . . . . . . . . . 17 2.2.3.2 Clustering-based Approach . . . . . . . . . . . . . . 20 Product Aspect Ranking . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.3.1 Related Work on Ranking of Reviews . . . . . . . . . . . . . . 24 2.3.2 Document-level Sentiment Classification . . . . . . . . . . . . 25 2.3.3 Extractive Review Summarization . . . . . . . . . . . . . . . . 25 Question Answering (QA) . . . . . . . . . . . . . . . . . . . . . . . . 26 2.4.1 Traditional QA . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.4.2 Opinion QA . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.4.2.1 Question Analysis and Answer Fragment Retrieval . . 28 2.4.2.2 Answer Generation . . . . . . . . . . . . . . . . . . 29 Chapter Hierarchical Organization of Consumer Reviews for Products 31 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.2 Hierarchical Organization Framework . . . . . . . . . . . . . . . . . . 35 3.2.1 Preliminary and Notations . . . . . . . . . . . . . . . . . . . . 36 3.2.2 Initial Hierarchy Acquisition . . . . . . . . . . . . . . . . . . . 37 3.2.3 Product Aspect Identification . . . . . . . . . . . . . . . . . . . 37 3.2.4 Generation of Aspect Hierarchy . . . . . . . . . . . . . . . . . 41 3.2.4.1 Formulation . . . . . . . . . . . . . . . . . . . . . . 41 3.2.4.2 Linguistic Features for Semantic Distance Estimation 44 3.2.4.3 Estimation of Semantic Distance . . . . . . . . . . . 46 Sentiment Classification on Product Aspects . . . . . . . . . . 48 Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.3.1 Data Set and Experimental Settings . . . . . . . . . . . . . . . 50 3.3.2 Evaluations on Product Aspect Identification of Free Text Reviews 52 3.3.3 Evaluations on Generation of Aspect Hierarchy . . . . . . . . . 53 3.3.3.1 53 3.2.5 3.3 Comparisons to the State-of-the-Art Methods . . . . vi 3.3.3.2 Evaluations on the Effectiveness of the Initial Hierarchy 55 3.3.3.3 Evaluations on the Effectiveness of Optimization Criteria 56 3.3.3.4 Evaluations on Semantic Distance Learning . . . . . 57 Evaluations on Aspect-level Sentiment Classification . . . . . . 59 Sub-tasks Reinforced by the Hierarchy . . . . . . . . . . . . . . . . . . 61 3.4.1 Product Aspect Identification with the Hierarchy . . . . . . . . 61 3.4.2 Sentiment Classification on Aspects using the Hierarchy . . . . 65 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.3.4 3.4 3.5 Chapter Product Aspect Ranking 69 4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.2 Product Aspect Ranking Framework . . . . . . . . . . . . . . . . . . . 72 4.2.1 Notations and Problem Formulation . . . . . . . . . . . . . . . 72 4.2.2 Aspect Ranking Algorithm . . . . . . . . . . . . . . . . . . . . 73 Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 4.3.1 Data Set and Experimental Settings . . . . . . . . . . . . . . . 76 4.3.2 Evaluations on Aspect Ranking . . . . . . . . . . . . . . . . . 77 Tasks Supported by Aspect Ranking . . . . . . . . . . . . . . . . . . . 81 4.4.1 Document-level Sentiment Classification . . . . . . . . . . . . 82 4.4.2 Extractive Review Summarization . . . . . . . . . . . . . . . . 85 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.3 4.4 4.5 Chapter Opinion Question Answering on Products 93 5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.2 Question Analysis and Answer Fragment Retrieval . . . . . . . . . . . 96 5.3 Answer Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.3.1 Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.3.2 Salience Weight Estimation . . . . . . . . . . . . . . . . . . . 102 vii 5.3.3 5.4 5.5 Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 5.4.1 Data Set and Experimental Settings . . . . . . . . . . . . . . . 104 5.4.2 Evaluations on Question Analysis . . . . . . . . . . . . . . . . 105 5.4.3 Evaluations on Answer Generation . . . . . . . . . . . . . . . 107 5.4.3.1 Comparisons to the State-of-the-Art Methods . . . . 107 5.4.3.2 Evaluations on the Effectiveness of Multiple Criteria . 109 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Chapter 6.1 Coherence Weight Estimation . . . . . . . . . . . . . . . . . . 103 Conclusions 111 Research Summary and Significance . . . . . . . . . . . . . . . . . . . 112 6.1.1 Hierarchical Organization of Consumer Reviews . . . . . . . . 112 6.1.2 Product Aspect Ranking . . . . . . . . . . . . . . . . . . . . . 113 6.1.3 Opinion-QA on Products . . . . . . . . . . . . . . . . . . . . . 114 6.2 Limitations of This Work . . . . . . . . . . . . . . . . . . . . . . . . . 114 6.3 Directions for Future Research . . . . . . . . . . . . . . . . . . . . . . 116 Bibliography 119 Publications 140 viii Abstract Huge collections of consumer reviews for products are now available on the Web. These reviews contain rich opinionated information on various products. They have become a valuable resource to facilitate consumers in understanding the products prior to making purchasing decisions, and support manufacturers in comprehending consumer opinions to effectively improve the product offerings. However, such reviews are often unorganized, leading to difficulty in information navigation and knowledge acquisition. It is inefficient for users to gather public opinions on a product by reading through all the consumer reviews and manually analyzing opinions on each review. To address the problem, this thesis focuses on discovering the natural structure inherent within the consumer reviews and organizing them accordingly. Since hierarchy can usually improve information dissemination and accessibility, we propose a domain-assisted approach to generate a hierarchical structure for organizing consumer reviews of products. The hierarchy is generated by simultaneously exploiting domain knowledge (e.g., the product specifications) and consumer reviews. It is a tree structure which organizes product aspects as nodes following their parent-child relations. The aspect refers to a component or an attribute of a certain product. For each aspect, the reviews and the corresponding opinions on this aspect are stored. Such hierarchy provides a well-visualized way to browse consumer reviews at different levels of granularity to meet various users’ information needs. With the hierarchy, users can easily grasp the overview of consumer reviews and conveniently seek the desired information, such as the product aspects and consumer opinions. We conduct experiments on 11 popular products in four domains. There are 70,359 consumer reviews on these products totally. This product review dataset has been released for future research. The experimental results demonstrate the effectiveness of the proposed approach. We further experimentally show that the generated hierarchy can reinforce the sub-tasks of product aspect identification ix and sentiment classification on aspects. The generated hierarchy can be used to support a wide range of tasks. In this thesis, we investigate its usefulness in supporting two tasks, i.e. product aspect ranking that aims to automatically identify important product aspects from consumer reviews, and opinion Question Answering (opinion-QA) on products which tries to generate appropriate answers for the opinionated questions about products. In particular, product aspect ranking identifies the important aspects according to two observations: (a) the important aspects of a product are usually commented by a large number of consumers; and (b) consumer opinions on the important aspects greatly influence their overall opinions on the product. Given the review hierarchy of a certain product, we develop an aspect ranking algorithm to identify the important aspects by simultaneously considering the aspect frequency and the influence of consumer opinions given to each aspect over their overall opinions. The experimental results on product review dataset illustrate the efficacy of the proposed aspect ranking approach. Furthermore, we leverage aspect ranking to support the sub-tasks of document-level sentiment classification and extractive review summarization. Significant performance improvements are achieved on these two sub-tasks. Additionally, we develop a new product opinion-QA framework with the help of the hierarchy, which enables accurate question analysis and effective answer generation. Specifically, we first identify the (explicit/implicit) product aspects asked in the questions and their sub-aspects by referring to the hierarchy. 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In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL’11, Oral), pp. 1496-1505, Portland, USA, June 19-24, 2011. [C1] Yu Jianxing, Zha Zheng-Jun, Wang Meng, and Chua Tat-Seng. Hierarchical Organization of Unstructured Consumer Reviews. In Proceedings of the 20th International World Wide Web Conference (WWW’11), pp. 171-172, India, Mar 28-Apr 1, 2011. [...]... browse consumer reviews at different levels of granularity to meet various users’ needs With the hierarchy, users can easily grasp the overview of consumer reviews and browse the desired information, such as product aspects and consumer opinions For example, users can find that 623 reviews, out of 9,245 reviews, are about the aspect “price”, with 241 positive and 382 negative reviews The hierarchical organization. .. There are often two kinds of information in the UGC, i.e the opinionated and factual information A process is needed to distinguish these two kinds of information Also, users are interested in various kinds of opinionated information on different UGC For example, they would concern product aspects for consumer reviews, and care opinion holders (i.e reviewers) or the hot events for news articles For this... the voice of the consumers from online reviews In addition, public opinions in the consumer reviews are all encoded in the hierarchy These opinions can be used to answer users’ opinionated questions about the products Opinionated questions often ask for consumers’ thinking and feeling on the products or aspects of products, such as “What’s everyone’s opinions on iPhone 4?” and the answer is formed by... acquisition It is impractical for users to grasp the overview of consumer reviews and opinions on various aspects of a product from such enormous reviews Among the hundreds of product aspects, it is also inefficient for users to browse consumer reviews and opinions on a certain aspect Thus, there is a compelling need to discover the structure within the consumer reviews and organize them accordingly,... important resource for both consumers and firms Consumers commonly seek quality information from online reviews prior to purchasing products, while many firms use online reviews as useful 3 feedbacks in their product development, marketing, and consumer relationship management 1.2 Motivation However, these numerous reviews are often unorganized, leading to the difficulty in information navigation and knowledge... platform for consumers to post reviews on millions of products For example, the forum CNet.com involves more 1 www.bing.com/shopping 2 Figure 1.1: Sample consumer reviews on website CNet.com than seven million product reviews [22]; whereas Pricegrabber.com contains millions of reviews on more than 32 million products in 20 distinct product categories over 11,000 merchants [101] Such numerous consumer reviews. .. contributions of this thesis are as follows: Hierarchical Organization of Consumer Reviews We propose a framework to generate a hierarchical structure to organize consumer reviews, so as to facilitate users in understanding the knowledge inherent within the reviews Moreover, we develop a domainassisted approach to generate the review hierarchy by exploiting domain knowledge and consumer reviews The generated... limitations of the work and possible directions for future research are demonstrated 11 Chapter 2 Literature Review This chapter reviews the related work to this thesis We first give an overview of current research topics on sentiment analysis We then illustrate the work related to three topics: (a) hierarchical organization of consumer reviews for products; (b) product aspect ranking; and (c) opinion-QA on products, ... understanding the knowledge inherent within the reviews Since the hierarchy can improve information dissemination and accessibility [20], we propose to generate a hierarchical structure to organize consumer reviews Figure 1.2 illustrates a sample of hierarchical organization for product iPhone 3G The hierarchy not only organizes all the product aspects and consumers’ opinions commented in the reviews, ... reviews into a hierarchy, and leverage the hierarchy to support the tasks of product aspect ranking and opinion-QA on products We outline the key ideas of these strategies in this Section and further detail them in Chapters 3, 4, and 5 7 respectively In particular, we propose a new framework for hierarchical organization of consumer reviews In the framework, we develop a domain-assisted approach to generate . HIERARCHICAL ORGANIZATION OF CONSUMER REVIEWS FOR PRODUCTS AND ITS APPLICATIONS YU JIANXING A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY SCHOOL OF COMPUTING NATIONAL UNIVERSITY OF. “call quality” of the product iPhone 3GS. Besides retail websites, many forum websites also provide a platform for consumers to post reviews on millions of products. For example, the forum CNet.com. the products. Opinionated questions often ask for consumers’ thinking and feeling on the products or aspects of products, such as “What’s everyone’s opinions on iPhone 4?” and the answer is formed