Opinion Mining with SentiWordNet

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Author(s): Bruno Ohana (Dublin Institute of Technology, Ireland)and Brendan Tierney (Dublin Institute of Technology, Ireland)
Copyright: 2011
Pages: 21
Source title: Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains
Source Author(s)/Editor(s): A.V. Senthil Kumar (CMS College of Science and Commerce, India)
DOI: 10.4018/978-1-60960-067-9.ch013

Keywords: Data Mining and Databases / Information Science Reference / Knowledge Discovery / Library & Information Science

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Abstract

Opinion Mining is an emerging field of research concerned with applying computational methods to the treatment of subjectivity in text, with a number of applications in fields such as recommendation systems, contextual advertising and business intelligence. In this chapter the authors survey the area of opinion mining and discuss the SentiWordNet lexicon of sentiment information for terms derived from WordNet. Furthermore, the results of their research in applying this lexicon to sentiment classification of film reviews along with a novel approach that leverages opinion lexicons to build a data set of features used as input to a supervised learning classifier are also presented. The results obtained are in line with other experiments based on manually built opinion lexicons with further improvements obtained by using the novel approach, and are indicative that lexicons built using semi supervised methods such as SentiWordNet can be an important resource in sentiment classification tasks. Considerations on future improvements are also presented based on a detailed analysis of classification results.

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