https://github.com/swapnanildutta/airline-tweets-visualization-web-app

This application is a Streamlit dashboard to analyze the sentiment of Tweets on Airlines.
https://github.com/swapnanildutta/airline-tweets-visualization-web-app

python python3 streamlit streamlit-dashboard streamlit-webapp visualization webapp

Last synced: 2 days ago
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This application is a Streamlit dashboard to analyze the sentiment of Tweets on Airlines.

• Host: GitHub
• URL: https://github.com/swapnanildutta/airline-tweets-visualization-web-app
• Owner: swapnanildutta
• License: mit
• Created: 2020-08-18T16:15:01.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-03-09T23:58:01.000Z (almost 2 years ago)
• Last Synced: 2024-11-10T19:50:55.609Z (2 months ago)
• Topics: python, python3, streamlit, streamlit-dashboard, streamlit-webapp, visualization, webapp
• Language: Python
• Homepage: https://airline-tweet-stat-app.herokuapp.com/
• Size: 2.7 MB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Airline-Tweets-Visualization-Web-App

[![HitCount](https://hits.dwyl.com/swapnanildutta/Airline-Tweets-Visualization-Web-App.svg)](http://hits.dwyl.com/swapnanildutta/Airline-Tweets-Visualization-Web-App)

[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)

## How to use

### Locally :

- Fork this repository and download using *git clone*.

    ```bash

    $git clone https://github.com//Airline-Tweets-Visualization-Web-App.git

    ```

- Install all the dependencies.

    ```powershell

    $pip install -r requirements.txt

    ```

    or,

    ```bash

    $pip3 install -r requirements.txt

    ```

- And, finally run the [app.py](app.py) file.

    ```bash

    $streamlit run app.py

    ```

### Remotely :

- Fork the repository and make necessary changes.

- Connect the web app to the repository.

## Output

### Tweets comparison by sentiment



    



### Tweets presented on map based on location and time.



    



### Raw Data



    



### Tweets comparison by Airline companies based on sentiment.



    



### WordCloud generated by Tweets of a particular Sentiment.