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The rapid growth of social media has led to an increase in user-generated content, making platforms like Twitter a major medium for public communication. However, along with positive engagement, there has also been a surge in hate speech, offensive language, and abusive content. This project aims to address this challenge by developing a ML program
KrishTalwar03/HATE_SPEECH_DETECTION
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# Hate Speech Detection A machine learning project for detecting hate speech in text using Decision Trees. ## Features - Text preprocessing with NLTK - TF-IDF vectorization - Decision Tree classifier with GridSearchCV - Confusion matrix visualization - Model persistence - Logging system - Object-oriented design ## Installation ```bash pip install -r requirements.txt ``` ## Usage ```bash python run_classifier.py ``` ## Project Structure - `hate_speech_classifier.py`: Main classifier implementation - `run_classifier.py`: Script to run the classifier - `models/`: Saved model files - `confusion_matrix.png`: Visualization output - `hate_speech_classifier.log`: Log file ## Requirements Create a requirements.txt file: ``` pandas numpy scikit-learn nltk seaborn matplotlib joblib ``` ## License MIT ## Author Krish Talwar
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The rapid growth of social media has led to an increase in user-generated content, making platforms like Twitter a major medium for public communication. However, along with positive engagement, there has also been a surge in hate speech, offensive language, and abusive content. This project aims to address this challenge by developing a ML program
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