yelp-revenge-sentiment

Detecting Revengeful Sentiment in Yelp Reviews Using Large Language Models

Description

This project aims to detect and analyze revenge-driven sentiment in Yelp reviews using large language models (LLMs). Unlike traditional sentiment analysis, which focuses on polarity (positive/negative), this approach seeks to uncover emotionally charged reviews motivated by retaliation, personal vendettas, or exaggerated negativity. The goal is to build a pipeline that can identify these nuanced signals and support deeper understanding of user intent.

Setup

1. Clone the repository:
   git clone https://github.com/your-username/yelp-revenge-sentiment.git
cd yelp-revenge-sentiment
2. Create virtual environment:
   python -m venv venv
3. Activate environment:
   .\venv\Scripts\activate
4. Install dependencies:
   pip install -r requirements.txt

Project Structure

• data/: Raw and processed Yelp datasets (.json, .json.gz)
• notebooks/: Exploratory analysis and model development in Jupyter
• src/: Core source code including data loaders, preprocessing, and modeling
• tests/: Unit tests for key components
• models/: Saved model checkpoints and outputs
• reports/: Generated reports, visualizations, and summaries
• .env: Environment variables
• requirement.txt: Python dependencies
• setup.py: Project packaging and metadata