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| title: MicroAggression Tool | |
| emoji: 📚 | |
| colorFrom: pink | |
| colorTo: indigo | |
| sdk: streamlit | |
| sdk_version: 1.42.0 | |
| app_file: app.py | |
| pinned: false | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| MicroAggression Insight Tool | |
| 📌 An AI-powered tool for analyzing, categorizing, and visualizing microaggressions based on sentiment and NLP processing. | |
| 🔍 Project Overview | |
| The MicroAggression Insight Tool is a research-driven web app that: | |
| ✅ Collects user-reported microaggression experiences | |
| ✅ Analyzes sentiment polarity (negative, neutral, positive) | |
| ✅ Categorizes microaggressions into: Microinvalidation, Microinsult, Microassault | |
| ✅ Visualizes trends using bar charts & word clouds | |
| ✅ Supports social psychology & intergroup relations research | |
| This project aligns with social psychology research on discrimination perception and consequences, specifically for microaggressions in different social contexts. | |
| 🎯 How to Use the App | |
| 1️⃣ Enter a statement (e.g., “You’re so articulate for someone like you”) | |
| 2️⃣ Click Analyze | |
| 3️⃣ The app will: | |
| • Categorize the statement into Microinvalidation, Microinsult, or Microassault | |
| • Analyze Sentiment (-1 = Negative, 0 = Neutral, +1 = Positive) | |
| • Visualize common patterns across all collected data | |
| 🔗 Live App: Check it out on Hugging Face Spaces | |
| 🖥️ Installation & Running Locally | |
| 🔧 If you want to run this app on your local machine, follow these steps: | |
| 1. Clone the Repository | |
| git clone https://github.com/durganihantri/MicroAggression-Insight-Tool.git | |
| cd MicroAggression-Insight-Tool | |
| 2. Create a Virtual Environment (Optional) | |
| python -m venv venv | |
| source venv/bin/activate # On Mac/Linux | |
| venv\Scripts\activate # On Windows | |
| 3. Install Dependencies | |
| pip install -r requirements.txt | |
| 4. Run the Streamlit App | |
| streamlit run app.py | |
| ✅ The app will launch in your browser at http://localhost:8501. | |
| 🚀 Deployment on Hugging Face Spaces | |
| If you want to deploy this app on Hugging Face Spaces, follow these steps: | |
| 1️⃣ Go to Hugging Face Spaces | |
| 2️⃣ Click “Create new Space” | |
| 3️⃣ Set SDK to Streamlit | |
| 4️⃣ Upload these files: | |
| • app.py (Main Streamlit app) | |
| • requirements.txt (Dependencies) | |
| 5️⃣ Click “Commit” and wait for the app to deploy. | |
| 🔗 Live App URL: Your Hugging Face Spaces Link | |
| 🛠️ Technical Details | |
| • Framework: Streamlit | |
| • Backend: Python (NLTK, TextBlob for NLP processing) | |
| • Data Storage: CSV-based (for collecting user input) | |
| • Visualization: Matplotlib, WordCloud | |
| • Modeling Techniques: | |
| • Sentiment Analysis via TextBlob | |
| • Categorization via basic NLP keyword matching | |
| 📌 Features & Future Enhancements | |
| ✅ Current Features | |
| ✔️ Microaggression categorization (Microinvalidation, Microinsult, Microassault) | |
| ✔️ Sentiment analysis for emotional impact | |
| ✔️ Bar chart & word cloud visualizations | |
| ✔️ User-reported microaggressions database | |
| 🔥 Planned Enhancements | |
| 🚀 Improve NLP classification (use GPT-based models for better accuracy) | |
| 🚀 Add multilingual support (expand analysis to other languages) | |
| 🚀 Integrate advanced analytics (e.g., time trends, deeper sentiment shifts) | |
| 🚀 Export reports for researchers (downloadable CSV files) | |
| 🧑💻 Author & Contact | |
| 👤 Developed by: Durganihantri | |
| 💡 For inquiries, research collaboration, or feedback: | |
| 📧 Email: [email protected] | |
| 🔗 LinkedIn: http://linkedin.com/in/durganihantri | |
| ⭐ Contribute & Support | |
| If you find this project useful, please consider starring the repo ⭐ and contributing! | |
| 📌 To contribute: | |
| • Fork this repository | |
| • Make improvements | |
| • Submit a Pull Request! |