Detection of Opinion: Approach based on Corpus vs. Approach based on SentiWordNet

Detection of Opinion: Approach based on Corpus vs. Approach based on SentiWordNet

Mohamed Amine Boudia (GeCoDe Laboratory, Dr. Moulay Tahar University of Saïda, Saïda, Algeria), Reda Mohamed Hamou (GeCoDe Laboratory, Dr. Moulay Tahar University of Saïda, Saïda, Algeria) and Abdelmalek Amine (GeCoDe Laboratory, Dr. Moulay Tahar University of Saïda, Saïda, Algeria)
DOI: 10.4018/IJOCI.2015040102
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Abstract

Opinion Mining is an area that has attracted many researchers, which resulted in several works. There are two types of approaches for detecting opinion: Approaches based on the corpus (Corpus-based Approach) and other approaches based on dictionary (Dictionary-based Approach). In this article, the authors will make a comparative study between the two approaches: the Bayesian method of Turney for the first approach; for the second approach, the authors will study the detection of opinion by the SentiWordNet and then the introduction of fuzzy logic is seen in this method. This study aims to study the theoretical and practical limitations of these two approaches.
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2. State Of Art

Opinion Mining is an area that has attracted many researchers which resulted in several works. There are two types of approaches for detecting opinion: Approaches based on corpus (Corpus-based Approach) which is to assign data to a supervised or unsupervised classification, this latter generates a model that is used to be tested, the most important works in this part approach: (Corbonell 1979)[1] optimized (Pereira et al, 1993) [2] improved by (Lin, 1998)[3], (Pang et al 2002) [4] (Yi et al, 2003) [5] (Yu and Hatzivassiloglou, 2003) [6]; (Wilson et al 2004) [7] (Kanayama and Nasukawa, 2006) [8] (Ding and Liu, 2007) [9] .

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