{"id":42457181,"url":"https://github.com/abh3shek/sentiment_analysis","last_synced_at":"2026-01-28T09:01:30.953Z","repository":{"id":321413359,"uuid":"1085739380","full_name":"Abh3shek/sentiment_analysis","owner":"Abh3shek","description":"A simple web app built with Streamlit that predicts the sentiment of a text as Positive or Negative. Uses NLTK for text preprocessing (stopword removal \u0026 stemming) and a trained Naive Bayes model for prediction. 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Originally trained on movie reviews, but it can handle general text statements as well.\n\n## Features\n\n- Text preprocessing using **NLTK**:\n  - Lowercasing\n  - Removing HTML tags and special characters\n  - Stopword removal\n  - Stemming with **Porter Stemmer**\n- Sentiment prediction using a pre-trained **Naive Bayes model**\n- Real-time predictions via a **user-friendly Streamlit interface**\n\n## Installation\n\n1. Clone the repository:\n\n   ```\n   git clone https://github.com/Abh3shek/sentiment_analysis.git\n   cd sentiment_classifier\n   ```\n\n2. Create a virtual environment (optional but recommended):\n\n   ```\n   python -m venv venv\n   source venv/bin/activate  # Linux/Mac\n   venv\\Scripts\\activate     # Windows\n   ```\n\n3. Install Dependencies:\n\n   ```\n   pip install -r requirements.txt\n   ```\n\n4. Ensure the `Model/` contains:\n\n   ```\n   - vectorizer.joblib\n   - model.joblib\n   ```\n\n5. Run:\n   `    streamlit run app.py\n   `\n   Open your browser at the URL provided (usually http://localhost:8501) and enter a text to get the sentiment prediction.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabh3shek%2Fsentiment_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabh3shek%2Fsentiment_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabh3shek%2Fsentiment_analysis/lists"}