{"id":22774919,"url":"https://github.com/prem07a/twittersentiment","last_synced_at":"2025-03-30T13:12:58.544Z","repository":{"id":213283159,"uuid":"733478395","full_name":"Prem07a/TwitterSentiment","owner":"Prem07a","description":"Analyzing Twitter sentiments with NLP deployed on Streamlit. 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The application is deployed using Streamlit, allowing users to interact with the sentiment analysis model through a user-friendly interface.\n\n## Table of Contents\n\n- [Overview](#overview)\n- [Project Structure](#project-structure)\n- [Setup](#setup)\n- [Usage](#usage)\n- [Demo](#demo)\n- [License](#license)\n\n## Project Structure\n\n- **app.py**: Streamlit application script containing the main logic for the sentiment analysis tool.\n- **models/**: Directory containing NLP model files or information.\n- **requirements.txt**: File listing required dependencies for the project.\n- **LICENSE**: License file for the project.\n\n## Setup\n\nTo run the project locally, follow these steps:\n\n1. Clone the repository:\n\n    ```bash\n    git clone https://github.com/Prem07a/TwitterSentiment.git\n    cd TwitterSentiment\n    ```\n\n2. Install dependencies:\n\n    ```bash\n    pip install -r requirements.txt\n    ```\n\n## Usage\n\nRun the Streamlit app with the following command:\n\n```bash\nstreamlit run app.py\n```\n\nAccess the application in your web browser at `http://localhost:8501`. Interact with the sentiment analysis tool to analyze Twitter text for sentiment.\n\n## Demo\n\n#### 1. Negative Tweet\n\u003cimg src=\"./image/neg_demo.png\"\u003e\n\n#### 2. Positive Tweet\n\u003cimg src=\"./image/pos_demo.png\"\u003e\n\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n```\n\n@Prem Gaikwad 2023\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprem07a%2Ftwittersentiment","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprem07a%2Ftwittersentiment","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprem07a%2Ftwittersentiment/lists"}