IBM Hack Challenge 2020

COVID-19-Sentiment-Analysis-Dashboard

Team: Bruteforce

An Auto-Updating Dynamic Covid-19 Sentiment Analysis Dashboard made using Django. Please visit here: https://c19dashboard.eu-gb.mybluemix.net/

Table Of Contents:

• Important Links For Judges
• About
• Usage
• Features
• Team Members
• Setup and Building Locally

Important Links For Judges:

• Website Link
• YouTube Video Presentation Link
• Google Slides Presentation Link
• Project Report Link
• Source Code

About:

• A dynamic auto-updating dashboard, monitoring tweets made with hashtags such as #indialockdown, #Covid19, #IndiaFightsCOVID19.
• The web application has the facility to provide Real-time visualizations for sentiments of the general public towards multiple topics such as 'Lockdown', 'Covid-19', 'UnlockIndia' and will not be limited to above topics.
• Sentiments such as Positive, Neutral and Negative are provided. The tweets are further classified into following categories:
  • Joy
  • Fear
  • Sadness
  • Analytical
  • Anger
  • Confident
• Real-time Trends of Sentiments over time, Most used Hashtags and distribution of Sentiments across India are displayed using intuitive visualizations.
• Real-time Covid-19 cases count with line charts and twitter feed by relevant handles are also displayed.
• On-demand sentiment analysis and twitter timelines of twitter handles are also displayed.
• The web application is developed using the Django Web Framework.

Usage:

General Page

Get instant live feed of sentiments across country towards topics related to the Covid-19 Pandemic.

Get the distribution of sentiments across states of India.

Sentiment Graphs Page

Get the trends of distribution of sentiments over time.

Covid 19 Updates Page

Get the latest count of Covid-19 cases, deaths, recovered and active patients.

Get state-wise count of Covid-19 cases.

Tweet Analysis page

Get the sentiment analysis of the last 100 tweets by any twitter handle instantly.

Features:

• Django-based backend

  • Django
  • Python 3.6 or later

• Frontend app(webapp) with HTML, JavaScript and CSS

  • Responsive UI with Bootstrap
  • Chart.js and HighCharts for charts and graphs.

• Data Analysis Tools used

  • numpy, pandas
  • VADER Sentiment Analysis
  • Watson Tone Analyser

• Deployment

  • IBM Cloud
  • Docker integration

Team Members:

• Atharva Lipare

• Naad Borole

Setup and Building Locally:

To clone the project:

git clone https://github.com/SmartPracticeschool/SBSPS-Challenge-1385-COVID-19-Sentiment-Analysis-Dashboard.git

From project root, you can download the project dependencies with:

cd c19Dashboard
pipenv install

To run your application locally:

python manage.py start

IBM Cloud Developer Tools

Install IBM Cloud Developer Tools on your machine by running the following command:

curl -sL https://ibm.biz/idt-installer | bash

Create an application on IBM Cloud by running:

ibmcloud dev create

This will create and download a starter application with the necessary files needed for local development and deployment.

Your application will be compiled with Docker containers. To compile and run your app, run:

ibmcloud dev build
ibmcloud dev run