Fake Reviews Detection Based on Sentiment Analysis Using ML Classifiers

Fake reviews carry substantial amount of significance for both the consumers and business owners and thus detection of fake reviews early helps to reduce the negative influential growth has become crucial after increased popularity of online shopping. Here, in this paper we propose machine learning approach by analysing both, the text and behaviour. A dataset of reviews was collected from various sites and it was labelled as Real or Fake. We then used various machine learning approaches like the Support Vector Machine, Logistic Regression and Multinomial Naive Bayes for training and evaluation of the performance of our model. Results show that our method provides accuracy at par with the existing ones. Our method has its utilization by businesses and review platforms to detect and remove fake reviews which enhances trust in online reviews. The developed system achieves a high accuracy rate of 85% in identifying fake reviews, demonstrating its effectiveness in improving the reliability of online reviews.