Fake Product Review Detection Using Machine Learning

• Author(s):

  Prabu P Asst.Prof. | Sreeram R, Naveen K | Tamilkumaran V | Sarvesh

• Keywords:

  E-commerce, FastAPI, Fake Reviews, Machine Learning, Natural Language Processing, Random Forest, React.js, Text Classification, Web Scraping

• Abstract:

  In The Digital Marketplace, Online Reviews Are A Key Factor In Shaping Consumer Decisions. However, The Prevalence Of Fake Reviews—either Overly Positive Or Deceptively Negative—threatens The Reliability Of Such Feedback. This Paper Presents A Machine Learning-based Solution Integrated Into A Web-based System For Detecting Fake Product Reviews. The System Accepts A Product URL, Scrapes Associated Reviews, Processes The Text Using Natural Language Processing (NLP) Techniques, And Classifies Them As Genuine Or Fake Using A Trained Model. We Implemented The System Using React.js For The Frontend, FastAPI For The Backend, And A Scikit-learn-based Random Forest Classifier. The Model Achieved 91% Accuracy On A Labeled Dataset, Demonstrating The Practical Feasibility Of Such A System For Real-world Deployment.

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Other Details

• Paper id:

  IJSARTV11I4103241

• Published in:

  Volume: 11 Issue: 4 April 2025

• Publication Date:

  2025-04-21

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