Abstract
As the Internet is evolving at a steeper rate, reviews related to a product have become a vital data which help users to make informed decisions. Users are totally dependent upon those reviews given by customers with the experience they felt and makers depend on these user-generated reviews to apprehend the sentiments of users related to a product. Henceforth, it is mandatory for both makers and users to create a portal where customers can peruse all the reviews in a comprehensive manner in a less amount of time. Considering this, a predictive model is developed that detects false positive reviews from original reviews and ratings are calculated to judge how these fake reviews create confusion in the mind of customers.
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Gaurav, D., Yadav, J.K.P.S., Kaliyar, R.K., Goyal, A. (2019). Detection of False Positive Situation in Review Mining. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 900. Springer, Singapore. https://doi.org/10.1007/978-981-13-3600-3_8
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DOI: https://doi.org/10.1007/978-981-13-3600-3_8
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