( ISSN 2277 - 9809 (online) ISSN 2348 - 9359 (Print) ) New DOI : 10.32804/IRJMSH

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STUDYING THE EFFECTIVENESS OF SUPERVISED CLASSIFICATION ALGORITHMS IN DETECTING FAKE ONLINE REVIEWS

    1 Author(s):  SAUMYA SATIJA

Vol -  13, Issue- 4 ,         Page(s) : 284 - 291  (2022 ) DOI : https://doi.org/10.32804/IRJMSH

Abstract

In this era of digitization Direct-to-Consumer (D2C) is a fast-track retail model which helps businesses sell items directly to clienteles via an online storefront, evading the chain of market intermediaries. The potential customers tend to make purchase decision according to the online reviews of the products. However, driven by profit, spammers post fake reviews to mislead the customers by promoting or demoting target product or services offered online. As there is no mechanism to control the reviews posted, anybody can write anything pseudonymously which conclusively leads to fake reviews.

[1] Elmogy, Ahmed & Tariq, Usman & Mohammed, Ammar & Ibrahim, Atef. (2021). Fake Reviews Detection using Supervised Machine Learning. International Journal of Advanced Computer Science and Applications. 12. 10.14569/IJACSA.2021.0120169.  
[2] Elmurngi, Elshrif & Gherbi, Abdelouahed. (2018). Detecting Fake Reviews through Sentiment Analysis Using Machine Learning Techniques.
[3] Ashwini.M.C et al, International Journal of Computer Science and Mobile Computing, Vol.9 Issue.7, July- 2020, pg. 97-108

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