Feature-based opinion mining through ontologies |
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| Affiliation: | 1. Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain;2. Computer Science Department, Universidad Carlos III de Madrid, Av. Universidad 30, Leganés, 28911 Madrid, Spain;1. Grup de Recerca en Sistemes Intel·ligents, Ramon Llull University, Quatre Camins 2, 08022 Barcelona, Spain;2. Grup de Recerca en Internet Technologies & Storage, Ramon Llull University, Quatre Camins 2, 08022 Barcelona, Spain;3. Departamento de Ingeniería Matemática e Informática, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Spain;1. Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia;2. Odette School of Business, University of Windsor, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada;1. Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, Niš, Serbia;2. Faculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 14, Niš, Serbia;1. School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China;2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton T6R 2V4 AB, Canada;3. School of Information, Liaoning University, Shenyang 110036, China;1. Center for Advanced Information Technology, Kyung Hee University, South Korea;2. School of Management, Kyung Hee University, South Korea |
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| Abstract: | The idiosyncrasy of the Web has, in the last few years, been altered by Web 2.0 technologies and applications and the advent of the so-called Social Web. While users were merely information consumers in the traditional Web, they play a much more active role in the Social Web since they are now also data providers. The mass involved in the process of creating Web content has led many public and private organizations to focus their attention on analyzing this content in order to ascertain the general public’s opinions as regards a number of topics. Given the current Web size and growth rate, automated techniques are essential if practical and scalable solutions are to be obtained. Opinion mining is a highly active research field that comprises natural language processing, computational linguistics and text analysis techniques with the aim of extracting various kinds of added-value and informational elements from users’ opinions. However, current opinion mining approaches are hampered by a number of drawbacks such as the absence of semantic relations between concepts in feature search processes or the lack of advanced mathematical methods in sentiment analysis processes. In this paper we propose an innovative opinion mining methodology that takes advantage of new Semantic Web-guided solutions to enhance the results obtained with traditional natural language processing techniques and sentiment analysis processes. The main goals of the proposed methodology are: (1) to improve feature-based opinion mining by using ontologies at the feature selection stage, and (2) to provide a new vector analysis-based method for sentiment analysis. The methodology has been implemented and thoroughly tested in a real-world movie review-themed scenario, yielding very promising results when compared with other conventional approaches. |
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| Keywords: | Opinion mining Ontology Sentiment analysis Feature extraction Part of speech tagging Polarity identification |
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