Feedback and Emotion Polarity Extraction from Online Reviewer Sites
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 9
Abstract
This research proposed collection of words and dictionary lookup based reviewer content emotion positive-negative polarity estimation technique from text. The restaurant review comments, feedback, notes, discussion and forum board data was obtained from various restaurant review web sites, blogs, forums and rating sites. The collection-bag of words and dictionary search of positive and negative words was constructed. In the next processing stage, the polarity of reviewed emotions was predicted using a bag of words and dictionary representing positive and negative emotions. The processing and estimation accuracy was examined and checked using the test data, by categorizing the split-tokenized test content into positive and negative reviews and positive and negative emotions and then was compared with human intervened annotation. The prediction results showed 81% accuracy in case of positive reviews and 83% accuracy in case of negative reviews.
Authors and Affiliations
Amol S Patwardhan
Keywords
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