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Reputation reporting system using text based classification
D. Jalther,
Published in Blue Eyes Intelligence Engineering and Sciences Publication
Volume: 8
Issue: 8
Pages: 1555 - 1558
Reputation System is a system which allow users to rate and review an organization or a product so that other users or customers can judge an organization or a product be seeing the reviews and ratings of an organization or a product. But the predictive value of reputation reporting system can be manipulated either by buyers or competitors to promote or demote a product or an organization. Fake review detection has attracted significant research attention in recent years. Some research has been done using dataset produced by fake review generator which was found inefficient. Some research has been done using behavioral pattern of spammers and pattern of fake reviews written which has produced some better results. In this paper, we implemented an approach to detect biased feedback using supervised machine learning algorithm. We used data from yelp.com which contains labelled dataset of restaurants in New York to train and test different classifier. In the end, we compared the accuracy of different classifiers to conclude which classifier has worked best on textual data. This model can be used by any service or product provider companies to detect and deleted biased feedback from their website. © BEIESP.
About the journal
JournalInternational Journal of Innovative Technology and Exploring Engineering
PublisherBlue Eyes Intelligence Engineering and Sciences Publication