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Added a template for hackathon submissions including sections for project details, tech stack, and links.
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Hackathon Submission:
fakeguard.zip
Fake Review Detection in Indian E-Commerce
Name
Vedant Pevekar
GitHub handle
@pevekarvedant22-create
Are you registered on our Hackathon Signup page?
This is a mandatory step for all participants to be considered eligible for judging
Project Description
Fake reviews have become a major challenge in Indian e-commerce platforms, influencing customer decisions and reducing trust in online marketplaces. This project uses Machine Learning and Natural Language Processing (NLP) techniques to automatically identify whether a review is genuine or fake.
The system analyses review text, extracts meaningful features, and predicts the authenticity of reviews. By detecting suspicious reviews, the solution helps customers make informed purchasing decisions and supports businesses in maintaining platform credibility.
Key Features
Real-time fake review detection
NLP-based text analysis
Machine Learning classification model
User-friendly web interface
Fast prediction results
Scalable for Indian e-commerce platforms
Supports trustworthy online shopping
Tech Stack
Frontend
HTML
CSS
JavaScript
Bootstrap
Backend
Python
Flask
Machine Learning & NLP
Scikit-learn
Pandas
NumPy
NLTK
Dataset
E-commerce Review Dataset
Kaggle Review Datasets
Tools
GitHub
VS Code
Jupyter Notebook
GitHub Repository
https://github.com/pevekarvedant22-create/fake-review-detection-indian-ecommerce
Live Demo
Problem Statement
Online platforms often suffer from fake reviews that mislead customers and reduce trust. Manual detection is difficult and time-consuming. This project automates the process of identifying suspicious reviews using AI and machine learning techniques.
Solution
The system preprocesses review text, extracts meaningful features using NLP techniques, and applies a trained machine learning model to classify reviews. Users can enter a review and instantly receive a prediction indicating whether the review is likely fake or genuine.
Future Improvements
Rules and Code of Conduct
By submitting this PR, you agree to follow our Rules and Code of Conduct.
Anything Else?
This project was developed to promote transparency and trust in online review systems. It demonstrates the practical use of Machine Learning and NLP in solving real-world problems related to digital commerce and user-generated content.
Thank you for organising this hackathon!