SentiPulse: Social Sentiment Analyzer

SentiPulse is an advanced sentiment analysis tool designed to quickly gauge public opinion from social media-style text inputs. It provides real-time sentiment analysis with a user-friendly interface, making it easy to understand the emotional tone of text data.

Table of Contents

• Features
• Tech Stack
• Prerequisites
• Installation
• Usage
• Project Structure
• API Endpoints
• Contributing
• License
• Contact
• Acknowledgements

Features

• Advanced Sentiment Analysis: Utilizes the distilroberta-base model from Hugging Face for accurate sentiment classification.
  • Classifies text into Positive, Negative, or Neutral categories.
  • Provides a confidence score for each classification.
• Fallback Mechanism: Implements a local, rule-based sentiment analysis as a backup when the Hugging Face API is unavailable.
• Real-time Processing: Instantly analyzes the sentiment of input text.
• Intuitive User Interface: Easy-to-use interface for entering text and viewing results.
• Visual Representation: Dynamic chart displaying sentiment distribution using Chart.js.
• Recent Analysis History: View a list of recent sentiment analyses stored in SQLite database.
• Responsive Design: Seamless experience across different device sizes.

Tech Stack

Backend

• Node.js: JavaScript runtime for server-side logic.
• Express: Web application framework for Node.js.
• SQLite: Lightweight, serverless database for data storage.
• Hugging Face Inference API:
  • Model: distilroberta-base
  • Task: Text Classification (Sentiment Analysis)
  • Capabilities: Multi-class classification (Positive, Negative, Neutral)
• dotenv: Environment variable management.

Frontend

• Svelte: Reactive JavaScript framework for building user interfaces.
• Vite: Next-generation frontend tooling for faster development.
• Chart.js: JavaScript charting library for data visualization.

Development Tools

• Git: Version control system.
• npm: Package manager for JavaScript.
• nodemon: Utility for automatic server restarts during development.

Prerequisites

• Node.js (v14 or later)
• npm (v6 or later)
• Git

Installation

1. Clone the repository:

   git clone https://github.com/ascender1729/sentipulse.git
   cd sentipulse
   

2. Install server dependencies:

   cd server
   npm install
   

3. Install client dependencies:

   cd ../client
   npm install
   

4. Set up environment variables:

   • Rename .env.example to .env in the server directory.
   • Add your Hugging Face API key to the .env file:

     HF_API_KEY=your_huggingface_api_key_here
     

Usage

1. Start the server:

   cd server
   npm run dev
   

2. In a new terminal, start the client:

   cd client
   npm run dev
   

3. Open your browser and navigate to http://localhost:5173.

4. Enter text in the input field and click "Analyze Sentiment" to see the results.

Project Structure

sentipulse/
├── server/
│   ├── src/
│   │   ├── config/
│   │   ├── controllers/
│   │   ├── routes/
│   │   ├── models/
│   │   └── index.js
│   └── package.json
├── client/
│   ├── src/
│   │   ├── components/
│   │   ├── App.svelte
│   │   └── main.js
│   ├── index.html
│   ├── package.json
│   └── vite.config.js
├── .env
├── .gitignore
└── README.md

API Endpoints

• POST /api/analyze: Analyze sentiment of provided text.
• GET /api/recent: Retrieve recent sentiment analyses.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Pavan Kumar - [email protected]

LinkedIn: linkedin.com/in/im-pavankumar

Project Link: https://github.com/ascender1729/sentipulse

Acknowledgements

• Hugging Face for their Inference API and the distilroberta-base model
• Svelte for the reactive UI framework
• Chart.js for data visualization
• Express.js for the server framework
• SQLite for the database