Detection Of Fake Review Using Machine Learning Classifiers: A Comparative Study

Abstract

The internet becomes quite important to our daily life. Whether it's trying to choose a service or a brand-new aesthetic. A lot of consumers’ decisions are based on these evaluations and opinions. Due to consumers' growing reliance on past user reviews over online platforms, scammers are overrunning the review system by posting fictitious reviews. Therefore, to save customer trust, automatic recognition of fraudulent reviews is much necessary. In this study, we have presented a machine learning-based model and compared the various classifiers cataboost classifier, linerSVC, SGD classifier, random forest classifier, multinomial NB, kneighbor classifier to separate genuine reviews from fake ones.