Rhibrahim15/hausa-sentiment-analysis

Machine learning project for sentiment analysis of Hausa text using TF-IDF and classification models. # hausa-sentiment-analysis Machine learning project for sentiment analysis of Hausa text using TF-IDF and classification models. # Hausa Sentiment Analysis using Machine Learning This project builds a machine learning model to classify Hausa text sentiment. The dataset used is from the NaijaSenti project which contains annotated Hausa tweets. Example: Ina son wannan fim → Positive Wannan abu ba shi da kyau → Negative Technologies Used Python Pandas Scikit-learn NLTK Project Structure data/ – raw dataset src/ – data preparation and model training scripts notebooks/ – exploratory data analysis Workflow 1. Load NaijaSenti dataset 2. Combine train, dev, and neutral datasets 3. Preprocess text 4. Convert text into TF-IDF features 5. Train sentiment classification model ## Model The trained sentiment classification model is saved as: model/sentiment_model.pkl This allows the model to be reused without retraining. Dataset Source NaijaSenti: A Nigerian Twit… Goal To explore Natural Language Processing techniques for African languages such as Hausa.