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README.md

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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+📖 AI-Powered Adaptive Reading Engagement Model
+
+🔍 Understanding Social Cognition & Reading Behavior in a Digital World
+
+📝 Overview
+
+The shift towards digital reading presents challenges and opportunities in how people engage with text. Many students struggle with reading motivation, comprehension, and goal-setting in digital environments. This project aims to analyze and enhance reading engagement using AI-powered Natural Language Processing (NLP), sentiment analysis, and emotion detection to create an adaptive reading system.
+
+🎯 Objectives
+
+✔ Analyze reading motivation & engagement in digital environments.
+✔ Detect emotions & sentiment from reading interactions.
+✔ Develop an adaptive reading model that adjusts text difficulty based on comprehension.
+✔ Encourage goal-setting in reading behavior using AI-generated feedback.
+
+This project aligns with research on social cognition and motivation sciences, contributing to educational psychology, digital literacy, and human-AI interaction studies.
+
+🚀 Features
+
+🔹 Sentiment & Emotion Detection – Uses NLP models to analyze user engagement.
+🔹 Adaptive Reading Level Detection – Adjusts difficulty based on comprehension.
+🔹 Reading Goal Tracker – Helps users track reading progress.
+🔹 AI-Powered Discussion Prompts – Generates thought-provoking questions to enhance engagement.
+🔹 Visual Analytics Dashboard – Displays engagement trends and sentiment scores.
+
+🧠 How the AI Works
+
+1️⃣ User selects or enters a text passage.
+2️⃣ AI analyzes the text using sentiment analysis (positive/negative/neutral).
+3️⃣ AI detects emotional engagement (e.g., joy, frustration, curiosity).
+4️⃣ System suggests adaptive modifications (simpler text for struggling readers, more complex text for advanced users).
+5️⃣ AI generates reflection prompts to encourage deeper engagement.
+6️⃣ A dashboard visualizes trends in reading engagement over time.
+
+💡 Research Applications
+
+This project can be used in:
+✔ Educational research – Understanding students’ digital reading behavior.
+✔ Cognitive psychology – Studying motivation & attention in reading.
+✔ AI in education – Exploring AI-enhanced literacy interventions.
+✔ Human-AI interaction – Investigating how AI influences reading engagement.
+
+📌 Installation Guide
+
+To run the app locally:
+
+1️⃣ Clone this repository
+
+git clone https://huggingface.co/spaces/Durganihantri/AI-Reading-Engagement
+cd AI-Reading-Engagement
+
+2️⃣ Install dependencies
+
+pip install -r requirements.txt
+
+3️⃣ Run the app
+
+streamlit run app.py
+
+4️⃣ View the app in your browser
+Go to http://localhost:8501/
+
+📊 Example Output
+
+🔹 Input Text:
+“Reading is an essential skill that shapes our understanding of the world.”
+
+🔹 Sentiment Analysis:
+✅ Positive: 85% | ❌ Negative: 5% | ⚪ Neutral: 10%
+
+🔹 Emotion Detection:
+🎭 Curiosity (70%), Engagement (65%), Frustration (5%)
+
+🔹 Adaptive Reading Suggestion:
+📖 “Try reading a related article on critical thinking in reading.”
+
+🔹 AI-Generated Reflection Prompt:
+🤔 “How does reading shape your perception of reality?”
+
+🌍 Try It Online
+
+👉 Live Demo on Hugging Face
+
+🛠 Technologies Used
+	•	Streamlit – Frontend UI
+	•	Transformers (Hugging Face) – NLP models for sentiment & emotion detection
+	•	NLTK & spaCy – Text preprocessing & sentiment analysis
+	•	Matplotlib – Data visualization
+	•	Python – Backend scripting
+
+🤝 Contributing
+
+We welcome contributions! You can:
+✔ Improve the adaptive learning model.
+✔ Enhance data visualization & analytics.
+✔ Expand the AI’s ability to suggest more personalized reading insights.
+
+Fork the repository and submit a pull request!
+
+📜 License
+
+This project is licensed under the MIT License.
+
+📬 Contact
+
+🔹 Author: Durganihantri
+🔹 Email: [email protected]
+🔹 LinkedIn: http://linkedin.com/in/durganihantri