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https://github.com/theinit01/twitter-hate-speech-classifier
A Machine Learning Model developed to detect and classify Hate Speech on Twitter built using streamlit
https://github.com/theinit01/twitter-hate-speech-classifier
decision-trees machine-learning python streamlit
Last synced: 12 days ago
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A Machine Learning Model developed to detect and classify Hate Speech on Twitter built using streamlit
- Host: GitHub
- URL: https://github.com/theinit01/twitter-hate-speech-classifier
- Owner: theinit01
- License: mit
- Created: 2024-03-26T07:40:43.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-08-05T10:16:15.000Z (3 months ago)
- Last Synced: 2024-08-05T11:57:18.945Z (3 months ago)
- Topics: decision-trees, machine-learning, python, streamlit
- Language: Jupyter Notebook
- Homepage:
- Size: 3.67 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Hate Speech Classifier
This repository contains a Streamlit web app for classifying tweets using a hate speech detection model. Users can input a Twitter handle, and the app gathers tweets associated with that handle. It then classifies the tweets into different categories using a machine learning model trained to detect hate speech.
## Features
- Allows users to input a Twitter handle.
- Gathers tweets associated with the input handle.
- Classifies tweets into categories using a hate speech detection model.
- Displays the number of tweets per category in a bar graph.
- Generates a word cloud visualization of the collected tweets.
- Shows a pie chart displaying the distribution of tweets by category.
## Setup
To run the Streamlit app locally, follow these steps:
1. Clone this repository:
```
git clone https://github.com/theinit01/Twitter-Hate-Speech-Classifier
```
2. Install the required dependencies:
```
pip install -r requirements.txt
```
3. Run the Streamlit app:
```
streamlit run model/webApp.py
```
## Usage
1. Enter a Twitter handle in the input field provided.
2. Wait for the app to gather tweets associated with the entered handle.
3. View the classification results in the form of a bar graph, word cloud, and pie chart.
4. Explore the sidebar for information about the hate speech detection model and hate speech.
## About
This project was developed as a part of our Mini Project. It demonstrates the use of machine learning for hate speech detection and provides an interactive web interface for users to explore the classification results.
## License
This project is licensed under the [MIT License](LICENSE).