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Supervised Machine Learning Based Approach to Detect Fake Online Hotel Reviews

	International Journal of Scientific Research and Engineering Development (IJSRED)	Full Text:
	Published Issue : Volume-4 Issue-2
	Year of Publication : 2021
	Unique Identification Number : IJSRED-V4I2P4
	Authors : Vijay, Shubham Kumar
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Abstract :

Online reviews regarding a product or a service influence the customers. Customers will always prefer to purchase the product which has good online reviews rather than the product having bad online reviews. Customers write online reviews to share their experiences which can be used by other customers for decision making regarding a particular product or service. Online reviews are very helpful in decision making if they are true. Sometimes people write fake reviews either to make their product or service popular or to mar the reputation of their competitors. Customers may regret in future if they make decisions on the basis of fake reviews. There is a need to detect fake online reviews. In this paper we used four machine learning based text classifiers to detect fake online reviews of hotels and discussed their performances. The four classifiers which we used in this paper are: Naïve Bayes, Random Forest, Support Vector Machine (SVM) and Classification and Regression Trees (CART). Among these four algorithms Naïve Bayes gave maximum accuracy. .