This repository contains the frontend and backend components of a real-time sentiment analysis application for Twitter data. The application is built using Angular, ExpressJS, and MongoDB.

This project aims to develop a web application for real-time sentiment analysis of tweets. The objective is to predict the sentiment (positive, negative, neutral, or irrelevant) of a given tweet.

The architecture of the project consists of the following elements:

1. Twitter Data Stream: Tweets are collected from a CSV file twitter_validation.csv.
2. Application Web: An Angular-based web application is used to visualize the test data and sentiment analysis results.

The tools and technologies used in this project include:

• Angular: For developing the user interface of the web application.
• ExpressJS: For creating the backend API that interacts with MongoDB.
• MongoDB: For storing the sentiment prediction results.
• Bootstrap: For developing a responsive and aesthetically pleasing user interface.

The frontend is developed using Angular and Bootstrap:

• Landing Page: Displays an overview of the application.
• Dashboard: Shows the sentiment analysis results and visualizations.

The backend is developed using ExpressJS and MongoDB:

• API Creation: ExpressJS is used to develop the backend API, handling requests and real-time predictions.
• Database Interaction: The API interacts with MongoDB to store and retrieve sentiment prediction results.