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Social Media Monitoring (SMM)

A comprehensive system for monitoring social media platforms, analyzing data, and providing insights using Electron, React, and Flask.

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Social Media Monitoring (SMM)

A comprehensive system for monitoring social media platforms, analyzing data, and providing insights using Electron, React, and Flask.

Project Overview

The Social Media Monitoring (SMM) project is designed to collect, analyze, and display social media data from platforms like X (formerly Twitter), Facebook, and Instagram. It consists of three main components:

  • Backend: A Flask-based backend responsible for scraping data, performing sentiment analysis, and sending alerts.
  • Frontend: An Electron-based desktop application to monitor and analyze the collected social media data.
  • User Site: A ReactJS-based web application that enables users to access and interact with the system.

🚀 Features

Data Collection and Analysis

  • Scraping data from multiple social media platforms
  • Sentiment analysis of collected data
  • Real-time alerts and notifications

User Interface

  • Desktop application for data monitoring
  • Web interface for user interactions
  • Interactive dashboards and reports

Integration and Automation

  • Seamless integration between frontend and backend
  • Automated data processing and analysis
  • API endpoints for external integrations

🛠 Tech Stack

  • Frontend: Electron, React.js
  • Backend: Flask
  • Data Processing: Python
  • Styling: CSS
  • State Management: Redux

Prerequisites

  • Python 3.7+ for the backend
  • Node.js for both the frontend (Electron) and the user site (ReactJS)
  • Virtual environment (recommended for the backend)

Installation

  1. Clone the repository:

    git clone https://github.com/amanjoshi2002/SMM-Social-Media-Monitoring-.git
cd SMM-Social-Media-Monitoring-

  2. Backend Setup:

    Follow the steps in the Backend README to set up the Flask server.

  3. Frontend Setup:

    Refer to the Frontend README for instructions to install and run the Electron app.

  4. User Site Setup:

    Visit the User Site README for steps to set up the ReactJS web app.

Running the Application

  1. Start the backend server:

    python run.py

  2. Start the frontend application:

    npm start

🔑 API Endpoints

Data Management

  • /api/start_scrapers - Initiates the data scraping process
  • /api/twitter_data - Retrieves Twitter data
  • /api/meta_data - Retrieves Meta data

User Interactions

  • /api/scrape - Scrapes user data based on input parameters

Middleware

  • CORS: Configured to allow specific origins.
  • Logging: Used for tracking API requests and responses.

Error Handling

The application includes error handling mechanisms to log errors and provide meaningful feedback to users.

License

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

Acknowledgments