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Volume 11, Issue 4 (April 2025)

Fake Product Review Detection Using Machine Learning

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7.883
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Volume 12 Issue 07

July 2026

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Author(s)

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

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.

Keywords

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

Paper ID

IJSARTV11I4103241

Publication Date

April 21, 2025

Research Area

Computer Science And Engineering

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