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10.5120/ijca2016910112 |
Mangal Singh, Tabrez Nafis and Neel Mani. Sentiment Analysis and Similarity Evaluation for Heterogeneous-Domain Product Reviews. International Journal of Computer Applications 144(2):16-19, June 2016. BibTeX
@article{10.5120/ijca2016910112, author = {Mangal Singh and Tabrez Nafis and Neel Mani}, title = {Sentiment Analysis and Similarity Evaluation for Heterogeneous-Domain Product Reviews}, journal = {International Journal of Computer Applications}, issue_date = {June 2016}, volume = {144}, number = {2}, month = {Jun}, year = {2016}, issn = {0975-8887}, pages = {16-19}, numpages = {4}, url = {http://www.ijcaonline.org/archives/volume144/number2/25151-2016910112}, doi = {10.5120/ijca2016910112}, publisher = {Foundation of Computer Science (FCS), NY, USA}, address = {New York, USA} }
Abstract
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.
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Keywords
Sentiment Vector, Intermediate Form, Sentiment Polarity Magnitude.