Spam Group Detection System: Enhancing Review Authenticity and Brand Credibility with NLP and Machine Learning

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Description

A system to detect and manage spam groups on online review platforms, enhancing review authenticity and brand credibility. It analyzes review data to identify suspicious user behavior using advanced NLP and machine learning techniques. The solution includes a Django web application and a PostgreSQL database for efficient data management and user interaction.
 

Practical Use Case and User Story

As a platform administrator, I want to detect and manage spam groups in Yelp reviews using NLP and machine learning models like Random Forest and KNN, so I can identify suspicious behaviors and maintain review authenticity. The system will preprocess review data, extract features, and classify potential spam. I can interact with the results through a Django web interface, storing data in PostgreSQL. The platform will visualize spam metrics and provide detailed reports for informed decision-making.

Tech Stack Involved

Programming Languages:
  • Python: For NLP, machine learning, and data processing.
  • JavaScript: For frontend interactions and dynamic content updates.
  • Libraries and Frameworks:
  • NLP Libraries: spaCy, NLTK, scikit-learn (for feature extraction and model training).
  • Machine Learning: scikit-learn (Random Forest, KNN).
  • Web Framework:
  • Django: For web application development and backend functionality.
Database:
  • PostgreSQL: For data storage and management.
  • PGAdmin: For database administration.
  • Data Processing:
  • pandas: For data manipulation and analysis.
  • numpy: For numerical operations.
  • networkx: For graph-based analysis of review behaviors.
User Interface:
  • HTML/CSS: For structuring and styling web pages.
  • JavaScript: For enhancing user interactions.
Deployment and Hosting:
  • Local Development: For initial testing and development.
  • (Optional) Cloud Platforms: Heroku, AWS, or DigitalOcean for production deployment.
Version Control:
  • Git: For managing code versions and collaboration.

Demo

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