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A full-stack web application designed to analyze and present sentiment and subjectivity from text within newspaper articles published across Africa

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African Sentiment News

African Sentiment News is a web application designed to present and analyze news articles published across Africa, with a focus on sentiment analysis to gauge public opinion and trends.

Features

  • Interactive display of news articles with sentiment analysis results.
  • Filtering options for articles by country, publisher, and sentiment score.
  • Line graphs depicting sentiment trends over time.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

What things you need to install the software and how to install them:

node.js
npm
git

Installing

A step by step series of examples that tell you how to get a development environment running:

Clone the repository:

git clone https://github.com/africansentiment/africansentiment-news.git

Install backend dependencies:

cd africansentiment-news/backend
npm install

Install frontend dependencies:

cd africansentiment-news/frontend
npm install

Running the application

To start the backend server:

npm run start-backend

To start the frontend application:

npm run start-frontend

Running the tests

Explain how to run the automated tests for this system:

npm run test-backend
npm run test-frontend
npm run test-e2e

Built With

  • React - The web framework used for the frontend
  • Node.js - The runtime server environment
  • Express - The backend framework
  • MongoDB - The database used
  • Cypress - The testing framework

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

  • Hat tip to anyone whose code was used
  • Inspiration
  • etc

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A full-stack web application designed to analyze and present sentiment and subjectivity from text within newspaper articles published across Africa

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