Context-Sensitive Opinion Mining using Polarity Patterns
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 9
Abstract
The growing of Web 2.0 has led to huge information is available. The analysis of this information can be very useful in various fields. In this regards, opinion mining and sentiment analysis are one of the most interesting task that many researchers have paid attention for two last decades. However, this task involves to some challenges that a very important challenge is the different polarity of words in various domain and context. Word polarity is an important feature in the determination of review polarity through sentiment analysis. Existing studies have proposed n-gram technique as a solution which allows the matching of the selected words to the lexicon. However, identification of word polarity using the standard n-gram method poses limitation as it ignores the word placement and its effect according to the contextual domain. Therefore, this study proposes a linguistic-based model to extract the word adjacency patterns to determine the review polarity. The results reflect the superiority of the proposed model compared to other benchmarking approaches.
Authors and Affiliations
Saeedeh Sadidpour, Hossein Shirazi, Nurfadhlina Sharef, Behrouz Minaei-Bidgoli, Mohammad Sanjaghi
Keywords
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- EP ID EP90984
- DOI 10.14569/IJACSA.2016.070920
- Views 141
- Downloads 0
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