HSTW
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Sentiment analysis tool aggregating world news, generating indices and displaying it all on a 3D globe.
🌍 How's The World 🌍
A sentiment analysis tool that aggregates news sources from around the world to generate a happiness index. This project aims at facilitating news consumption and to have a concentrate of all important news within a single glance. The project is built using a combination of Python Flask for the backend and React for the frontend.

Features
- Generates a happiness index based on the sentiment analysis of news headlines
- Visualizes the data on an easy-to-use dashboard
- Automated data collection process using web scraping techniques
- Responsive design, can be accessed on any mobile device
Technologies
- Backend: Python Flask, pandas, nltk, boto3, feedparser
- Frontend: React, react-router-dom, react-globe.gl, CSS, Chart.js
Installation
- Clone the repository
For Backend
- I recommend the usage of a virtual environment
- Install the dependencies using
pip install -r requirements.txt - You might have to install nltk additional dependencies manually with 'python -m nltk.downloader all'
For the Frontend
- Run the backend server using
flask run - Install the dependencies using
npm i - Run the frontend using
npm start
Usage
- Access the frontend at hstw.io
- Access the raw data at hstwdrop.co
Contributors Guide
- [ ] Reinforcement of the backend
- [ ] Updating the news sources
- [ ] Better impartiality in news source and fine-tuning of the scraping algorithm
- [ ] Development of the UI
- [ ] Addition of Chart.js visualisation
- [ ] Implementation of custom iPhone shortcuts for the visualization to be even faster and easier
- [ ] Instagram story generator for particular news that need extra-sharing
Contributing
- I am currently the sole contributor, but I welcome any contributions and suggestions from the community to improve and expand the capabilities of this tool
- Please feel free to submit a pull request or open an issue
License
- The project is not to be used for any commercial use wihout the prior agreement of the original Author
Author
❤️