Fake Review Detection System Using Machine Learning with source code and documents. It is full stack web application project with code and documents.

Detects fake product reviews using supervised ML algorithms like SVM, Random Forest, and XGBoost. Uses NLP techniques (tokenization, lemmatization, TF-IDF) for preprocessing. SVM achieved the highest accuracy and F1-score. Aims to enhance trust in online review systems.

Sentiment Analysis and Fake Review Analysis of Amazon Products using NLP with R

Protect your brand from misleading feedback by spotting fake product reviews automatically. This n8n workflow analyzes reviews with OpenAI, flags suspicious patterns, stores evidence in Airtable and sends instant Slack alerts. A practical n8n workflow template for review moderation, trust and quality control.