libanabduba/Afan-Oromo-Hate-Speech-Detection

# Afaan Oromo Hate Speech Detection (NLP Project) 🚫🗣️ ## Introduction 📝 This project aims to detect hate speech in Afaan Oromo language using Natural Language Processing (NLP) techniques. The code includes a Django web application with a hate speech detection model implemented in Keras. The hate speech detection model is trained on the "Afaan Oromo Hate Speech Dataset" available in the provided CSV file. ## Getting Started 🚀 ( Project Setup ) Follow these steps to set up and run the project: #### 1. Clone the Repository Clone this GitHub repository using the following command: ```bash git clone github.com ``` #### 2. Create Virtual Environment Create a virtual environment to run the project and download the project packages to avoid clashes with existing ones. Refer to the details in Python's venv documentation. #### 3. Install Dependencies Install the required Python packages using the following command: ```bash pip install -r requirements.txt ``` #### 4. Database Setup Run the following commands to apply migrations to the database: ```bash python manage.py makemigrations python manage.py migrate ``` #### 5. Superuser Setup Set up a superuser for the app. For Django, use the following command and fill in the details when prompted: ```bash python manage.py createsuperuser ``` #### 6. Run the App Now, run the app using the below command. ```bash python manage.py runserver ``` ## Text Preprocessing ✨ The `socials/base/utils.py` file contains functions for text preprocessing, including: - HTML tag removal ✂️ - Symbol and noise removal 🚮 - Stopword removal 🛑 - Non-alphanumeric word removal ❌ ## Hate Speech Detection 🚫🗣️ The hate speech detection model predicts whether a given post contains hate speech. The `Post` model in `socials/base/models.py` includes a method `predict_is_hate` that uses the loaded model to make predictions. ## Usage 💡 1. Integrate the provided code into your Django project. 2. Ensure the hate s …