{"id":21972885,"url":"https://github.com/rrayhka/sentiment-analisis-app","last_synced_at":"2026-04-29T20:06:11.321Z","repository":{"id":246211265,"uuid":"819847536","full_name":"rrayhka/sentiment-analisis-app","owner":"rrayhka","description":"Web-based sentiment analysis app using BiLSTM and Attention models for text sentiment classification.","archived":false,"fork":false,"pushed_at":"2024-08-15T14:18:22.000Z","size":6321,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-22T23:14:59.284Z","etag":null,"topics":["attention","bilstm","flask","nlp","sentiment-analysis"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rrayhka.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-06-25T10:01:02.000Z","updated_at":"2024-08-15T14:19:39.000Z","dependencies_parsed_at":"2024-08-15T16:19:16.913Z","dependency_job_id":null,"html_url":"https://github.com/rrayhka/sentiment-analisis-app","commit_stats":null,"previous_names":["rrayhka/sentiment-analisis-app"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rrayhka/sentiment-analisis-app","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rrayhka%2Fsentiment-analisis-app","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rrayhka%2Fsentiment-analisis-app/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rrayhka%2Fsentiment-analisis-app/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rrayhka%2Fsentiment-analisis-app/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rrayhka","download_url":"https://codeload.github.com/rrayhka/sentiment-analisis-app/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rrayhka%2Fsentiment-analisis-app/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32441498,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T18:12:22.909Z","status":"ssl_error","status_checked_at":"2026-04-29T18:11:33.322Z","response_time":110,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["attention","bilstm","flask","nlp","sentiment-analysis"],"created_at":"2024-11-29T15:22:22.640Z","updated_at":"2026-04-29T20:06:06.306Z","avatar_url":"https://github.com/rrayhka.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sentiment-Analysis-App\n\nThis repository contains a web-based sentiment analysis application that allows users to input text and choose between two different models for analysis: BiLSTM and Attention. The application provides a simple and interactive interface for sentiment analysis, enabling users to quickly determine the sentiment of a given sentence.\n\n## Table of Contents\n\n- [About](#about)\n- [Features](#features)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Project Structure](#project-structure)\n- [Contributing](#contributing)\n- [Contact](#contact)\n\n## About\n\nThe Sentiment-Analysis-App is designed to analyze the sentiment of text data using two state-of-the-art models: BiLSTM (Bidirectional Long Short-Term Memory) and Attention. The user can input a sentence through a web interface and select which model to use for the sentiment analysis.\n\n## Features\n\n- **Two Models:** Choose between BiLSTM and Attention models for sentiment analysis.\n- **User-Friendly Web Interface:** Simple input form for text and model selection.\n- **Real-Time Sentiment Analysis:** Displays the sentiment result immediately after submission.\n\n## Installation\n\n1. Clone the repository:\n\n    ```bash\n    git clone https://github.com/rrayhka/sentiment-analisis-app.git\n    cd sentiment-analisis-app\n    ```\n\n2. Run the web application:\n\n    ```bash\n    python app.py\n    ```\n\n## Usage\n\n1. **Accessing the Web Interface:**\n   - After running the application, open your web browser and navigate to `http://localhost:5000`.\n   \n2. **Performing Sentiment Analysis:**\n   - Enter the text you wish to analyze in the input field.\n   - Select either the BiLSTM or Attention model from the dropdown menu.\n   - Click \"Analyze Sentiment\" to receive the sentiment result.\n\n3. **Viewing Results:**\n   - The sentiment result will be displayed on the page, indicating whether the input text is positive, negative, or neutral.\n\n## Project Structure\n\n- `app.py`: The main Flask application file that runs the web interface.\n- `models/`: Directory containing pre-trained models (BiLSTM and Attention).\n - `nn.py`: Contains the neural network models and the logic for loading and predicting sentiment using BiLSTM and Attention models.\n- `notebooks/`: Contains Jupyter notebooks used for model training and evaluation.\n- `templates/`: HTML templates for the web interface.\n- `dataset/`: Contains the dataset used for training and testing.\n\n## Contributing\n\nContributions are welcome! If you have any suggestions, improvements, or bug fixes, feel free to submit a pull request or open an issue.\n\n1. Fork the repository.\n2. Create your feature branch (`git checkout -b feature/AmazingFeature`).\n3. Commit your changes (`git commit -m 'Add some AmazingFeature'`).\n4. Push to the branch (`git push origin feature/AmazingFeature`).\n5. Open a Pull Request.\n\n\n## Contact\n\nAkhyar - [khyar075@gmail.com](mailto:khyar075@gmail.com)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frrayhka%2Fsentiment-analisis-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frrayhka%2Fsentiment-analisis-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frrayhka%2Fsentiment-analisis-app/lists"}