https://github.com/hasanulmukit/multi-language-sentiment-analysis
An AI-powered web app for real-time sentiment analysis using Hugging Face Transformers and Streamlit.
https://github.com/hasanulmukit/multi-language-sentiment-analysis
artificial-intelligence huggingface machine-learning nlp python sentiment-analysis streamlit
Last synced: about 1 month ago
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An AI-powered web app for real-time sentiment analysis using Hugging Face Transformers and Streamlit.
- Host: GitHub
- URL: https://github.com/hasanulmukit/multi-language-sentiment-analysis
- Owner: hasanulmukit
- Created: 2025-01-29T08:09:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-08T06:10:55.000Z (over 1 year ago)
- Last Synced: 2025-03-29T05:17:51.929Z (about 1 year ago)
- Topics: artificial-intelligence, huggingface, machine-learning, nlp, python, sentiment-analysis, streamlit
- Language: Python
- Homepage:
- Size: 15.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Multi Language Sentiment Analysis
## 📌 Overview
This is a **Multi Language Sentiment Analysis App** built with **Streamlit** and **Hugging Face Transformers**. It allows users to analyze the sentiment (Positive, Negative) of any given text using **state-of-the-art NLP models**.
## 🚀 Features
- **Sentiment History** to track past analyses in a session.
- **Graphical Representation** of sentiment confidence using a progress bar.
- **Multi-Language Support** via Google Translate.
- **File Upload Support** for bulk sentiment analysis.
- **Download Results** as a CSV file.
- **Emoji-based Sentiment Display** for better UX.
## 🛠️ Installation
1. Clone the repository:
```bash
git clone https://github.com/hasanulmukit/sentiment-analysis-app.git
cd sentiment-analysis-app
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the app:
```bash
streamlit run app.py
```
## 📊 Usage
- **Enter Text**: Type or paste a sentence in the text area.
- **Analyze Sentiment**: Click the "Analyze" button to get sentiment results.
- **View History**: Check previous sentiment analyses.
- **Upload Files**: Upload `.txt` or `.csv` files for batch analysis.
- **Download Results**: Save the analysis as a CSV file.
## 🏗️ Technologies Used
- **Python** 🐍
- **Streamlit** 🎨 (for UI)
- **Transformers** 🤗 (Hugging Face NLP Models)
- **SpeechRecognition** 🎙️ (for voice input)
- **GoogleTrans** 🌍 (for multi-language support)
- **Matplotlib & Pandas** 📊 (for visualization & data processing)
## 🎯 Future Improvements
- Improve accuracy with fine-tuned models.
- Add support for more advanced NLP techniques.
- Deploy the app using Streamlit Cloud or Hugging Face Spaces.
## 💡 Contribution
Feel free to fork this repo, improve it, and submit a pull request! 🚀
## 📜 License
This project is licensed under the **MIT License**.
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