https://github.com/mantreshkhurana/twitter-toxicity-detection-flask

This is a simple python program which uses a machine learning model to detect toxicity in tweets, developed in Flask.
https://github.com/mantreshkhurana/twitter-toxicity-detection-flask

flask hate-speech-detection hate-speech-detection-flask linear-regression ml python scikit-learn sklearn toxicity-detection twitter-api

Last synced: 2 months ago
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This is a simple python program which uses a machine learning model to detect toxicity in tweets, developed in Flask.

Host: GitHub
URL: https://github.com/mantreshkhurana/twitter-toxicity-detection-flask
Owner: mantreshkhurana
License: mit
Created: 2023-05-02T19:31:01.000Z (about 2 years ago)
Default Branch: stable
Last Pushed: 2024-04-04T08:09:53.000Z (about 1 year ago)
Last Synced: 2024-05-02T04:39:20.339Z (about 1 year ago)
Topics: flask, hate-speech-detection, hate-speech-detection-flask, linear-regression, ml, python, scikit-learn, sklearn, toxicity-detection, twitter-api
Language: HTML
Homepage:
Size: 49 MB
Stars: 17
Watchers: 7
Forks: 3
Open Issues: 3
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE

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README

        

# Twitter Toxicity Detection Flask

This is a Flask web application that allows users to search for a Twitter user's recent tweets and get a toxicity score for each tweet using a pre-trained logistic regression model.

It has a [Window GUI](#window-gui) version which can also be used to do the same without opening the browser.

## Table of Contents

- [Twitter Toxicity Detection Flask](#twitter-toxicity-detection-flask)

  - [Demo](#demo)

    - [Demo Video](#demo-video)

    - [Screenshots](#screenshots)

    - [Pie Chart](#pie-chart)

    - [Window GUI](#window-gui)

  - [Installation](#installation)

    - [Virtual Environment](#virtual-environment)

    - [Locally](#locally)

  - [Usage](#usage)

  - [Features](#features)

  - [Project Structure](#project-structure)

  - [Contributing](#contributing)

  - [Author](#author)

## Demo

### Demo Video

https://github.com/mantreshkhurana/twitter-toxicity-detection-flask/assets/120998049/dba98bad-50d3-472c-bd22-e4cfe4282425

### Screenshots

| Light | Dark |

| :---: | :---: |

| ![App Screenshot](./assets/screenshots/screenshot-1-light.png) | ![App Screenshot](./assets/screenshots/screenshot-1-dark.png)

| ![App Screenshot](./assets/screenshots/screenshot-2-light.png) | ![App Screenshot](./assets/screenshots/screenshot-2-dark.png)

### Pie Chart

You can see a pie chart which portrays the percentage of tweets that are toxic and non-toxic. It can be viewed by clicking on the view Pie Chart button which is located bellow `following` and `followers` count



  



## API Keys Popup

After saving the API keys, you can close the popup and restart the flask server.

| Light | Dark |

| :---: | :---: |

| ![App Screenshot](./assets/screenshots/screenshot-5-popup-light.png) | ![App Screenshot](./assets/screenshots/screenshot-5-popup-dark.png)

### Window GUI

![App Screenshot](./assets/screenshots/screenshot-4-app.png)

## Installation

You may need to install some dependencies before running the program(some of the modules cannot be installed directly by using `requirements.txt`).

Get Twitter API keys from [here](https://developer.twitter.com/en/docs/twitter-api/getting-started/getting-access-to-the-twitter-api).

> **Note**: Make sure to apply for Twitter Elevated Access to use the Twitter API v2 endpoints, without elevated access you will not be able to use this app. (It's FREE until you reach the limit of 2,000,000 tweets per month)

To get started with this project, follow these steps:

### Virtual Environment

I recommend using a virtual environment for this project.

```bash

git clone https://github.com/mantreshkhurana/twitter-toxicity-detection-flask.git

cd twitter-toxicity-detection-flask

python -m venv venv

source venv/bin/activate

pip install -r requirements.txt

touch .env

echo "CONSUMER_KEY=" >> .env # replace  with your Twitter API consumer key

echo "CONSUMER_SECRET=" >> .env # replace  with your Twitter API consumer secret

echo "ACCESS_TOKEN=" >> .env # replace  with your Twitter API access token

echo "ACCESS_TOKEN_SECRET=" >> .env # replace  with your Twitter API access 

python app.py

```

### Locally

```bash

git clone https://github.com/mantreshkhurana/twitter-toxicity-detection-flask.git

cd twitter-toxicity-detection-flask

pip install -r requirements.txt

python setup.py # fill in the required details for Twitter API keys

python app.py

```

or

```bash

git clone https://github.com/mantreshkhurana/twitter-toxicity-detection-flask.git

cd twitter-toxicity-detection-flask

pip install -r requirements.txt

touch .env

echo "CONSUMER_KEY=" >> .env # replace  with your Twitter API consumer key

echo "CONSUMER_SECRET=" >> .env # replace  with your Twitter API consumer secret

echo "ACCESS_TOKEN=" >> .env # replace  with your Twitter API access token

echo "ACCESS_TOKEN_SECRET=" >> .env # replace  with your Twitter API access token secret

python app.py

```

or

```bash

git clone https://github.com/mantreshkhurana/twitter-toxicity-detection-flask.git

cd twitter-toxicity-detection-flask

pip3 install -r requirements.txt

touch .env

echo "CONSUMER_KEY=" >> .env # replace  with your Twitter API consumer key

echo "CONSUMER_SECRET=" >> .env # replace  with your Twitter API consumer secret

echo "ACCESS_TOKEN=" >> .env # replace  with your Twitter API access token

echo "ACCESS_TOKEN_SECRET=" >> .env # replace  with your Twitter API access token secret

python3 app.py

```

Navigate to [http://127.0.0.1:5000/](http://127.0.0.1:5000/) in your web browser to use the app, else `flask run -p 8000`.

## Usage

```bash

python app.py

```

If you want to run the app in a Window GUI:

```bash

python app.py --window

# or

python app.py -w

```

Use custom port:

```bash

python app.py --port 8000

# or

python app.py -p 8000

```

## Features

- [x] Search for a Twitter user's recent tweets.

- [x] Dark/Light mode.

- [x] View a pie chart for profile's toxicity.

- [x] View user's profile picture, name, username, bio, location, website, following, followers, and tweet count*.

- [x] View images/videos in tweets.

- [x] View retweets and likes count for each tweet.

- [x] View the date and time of each tweet.

- [x] View the source of each tweet.

- [x] Twitter like feed.

- [x] Simple bot protection.

- [x] GUI Window Added.

- [x] Dialog to store API Keys in `.env`.

- [ ] Images/Videos toxicity detection.

## Project Structure

```txt

twitter-toxicity-detection-flask/

├── app.py

├── models/

│   └── hate_speech_model.csv

├── static/

│   ├── css/

│   │   └── style.css

│   └── js/

│       └── script.js

├── templates/

│   ├── index.html

│   ├── results.html

│   └── error.html

├── .env

├── .gitignore

├── README.md

└── requirements.txt

```

## Contributing

Since this project took <12 hours to make you may find some bugs or you may want to add some features to it. You can contribute to this project by forking it and making a pull request(I am quite active on Github so if any issue arises I will try to fix it as soon as possible).

After forking:

```bash

git clone https://github.com//twitter-toxicity-detection-flask.git

cd twitter-toxicity-detection-flask

git checkout -b 

# after adding your changes

git add .

git commit -m "your commit message"

git push origin 

```

## Credits

- [Flask](https://www.fullstackpython.com/flask.html)

- [Twitter](https://twitter.com/)

- [Sklearn](https://scikit-learn.org/stable/)

- [Python](https://www.python.org/)

- [Tweepy](https://www.tweepy.org/)

- [pywebview](https://pywebview.flowrl.com/)

## Author

- [Mantresh Khurana](https://github.com/mantreshkhurana)

ecosyste.ms

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https://github.com/mantreshkhurana/twitter-toxicity-detection-flask

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