Employee Culling based on of Online Work Assessment through Machine Learning Algorithm

Abstract

Online reviews are one of the significant factors in a customer’s purchase decision or to avail of any service. Online reviews give rise to the potential threats that fake reviewers may write a false review to artificially promote a product or defaming value of a service. Using Natural Language Processing, many methods have already been developed to detect fake reviews, especially reviews written in the English language. In this paper, I propose a novel framework where authenticity of a feedback will check through two perspectives. Firstly, the system checks whether the review is fake or not. Secondly, it also checks the authenticity of the reviewer. The outcome result accumulates in cloud storage for providing further business analytics.