XSA - (X Sentiment Analysis) 📊🐦
Overview
Twitter Sentiment Analysis is a fundamental task in Natural Language Processing (NLP), involving the classification of tweets into positive, negative, or neutral sentiment categories. This project focuses on creating a user-friendly GUI application for sentiment analysis using custom-built machine learning algorithms.
Key Learning Objectives 🚀
- GUI Development: Create an intuitive Graphical User Interface (GUI) with Tkinter.
- Custom Sentiment Analysis: Implement sentiment analysis from scratch, avoiding pre-built NLP or ML libraries.
- Hands-on Machine Learning: Gain practical experience with machine learning algorithms for text classification.
- Python Proficiency: Enhance Python programming skills through real-world application development.
- Collaborative Project: Work on a group project in a university setting, fostering teamwork and learning dynamics.
Project Report 🛠️
Following is the official report for the project. (Translation in English is WIP)
Contributing 🤝
Contributions are welcome! If you have any suggestions, improvements, or feature requests, feel free to open an issue or create a pull request on the public repository @ (https://github.com/Jakcrimson/pjeb_twitter_sentiment_analysis)
License 📝
This project is licensed under the MIT License.
Acknowledgments 🙌
Special thanks to Paul-Henri ICHER (@PHITAJ) and Sebastian SAFARI (@sebss) for the contributions to this project!