International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 144 - Issue 2 |
Published: Jun 2016 |
Authors: Mangal Singh, Tabrez Nafis, Neel Mani |
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Mangal Singh, Tabrez Nafis, Neel Mani . Sentiment Analysis and Similarity Evaluation for Heterogeneous-Domain Product Reviews. International Journal of Computer Applications. 144, 2 (Jun 2016), 16-19. DOI=10.5120/ijca2016910112
@article{ 10.5120/ijca2016910112, author = { Mangal Singh,Tabrez Nafis,Neel Mani }, title = { Sentiment Analysis and Similarity Evaluation for Heterogeneous-Domain Product Reviews }, journal = { International Journal of Computer Applications }, year = { 2016 }, volume = { 144 }, number = { 2 }, pages = { 16-19 }, doi = { 10.5120/ijca2016910112 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2016 %A Mangal Singh %A Tabrez Nafis %A Neel Mani %T Sentiment Analysis and Similarity Evaluation for Heterogeneous-Domain Product Reviews%T %J International Journal of Computer Applications %V 144 %N 2 %P 16-19 %R 10.5120/ijca2016910112 %I Foundation of Computer Science (FCS), NY, USA
Sentiment analysis and classification is a prominent research topic in academics as well as in industrial field. Since each customer reviews text always state emotion about a target domain, sentiment classification is a highly domain dependent task and present study considered the reviews from heterogeneous domains. Generally researchers classify the customer review with positive, negative and neutral sentiments but a positive review can be highly positive and a negative review can be highly negative, so sentiment analysis about a review can be more effective if a sentiment scale is also defined for such greater degree of positivity or negativity. We defined a framework to classify heterogeneous product reviews with degree of polarity on a sentiment scale of range -2 to 2. For each review, an intermediate form is calculated using sentiment vectors which is further processed to calculate the sentiment polarity magnitude and similarity of reviews.