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--- |
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title: TextBlobSentimentAnalysis |
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emoji: 📈 |
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colorFrom: yellow |
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colorTo: purple |
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sdk: streamlit |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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short_description: 'Kid safe Text Mood Detector ' |
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--- |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
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# Keyur-Jotaniya-mood2emoji |
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Kid-safe Text-Mood Detector (Streamlit + TextBlob or rule-based) |
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# Kid-safe Text-Mood Detector |
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A simple Streamlit + TextBlob app for kids |
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## What this project does |
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This web app takes a text and predicts the **mood** behind it using **TextBlob sentiment analysis**. |
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| Mood | Emoji | Example Output | |
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--------------------------------- |
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| Happy | 😀 | "Happy" | |
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| Neutral | 😐 | "Neutral" | |
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| Sad | 😞 | "Sad" | |
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| Inappropriate | ⚠️ | "Inappropriate words" | |
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| Empty Input | 🥱 | "Empty text — Please write something to analyze" | |
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This app helps kids safely understand and have fun with Natural Language Processing (NLP). |
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## How kids learn from it |
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1. Experiment with how computers “read” emotions from text. |
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2. See how simple **thresholds** (+0.3 / -0.3) decide between *happy, sad, or neutral*. |
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3. Learn about **safe and responsible AI** — understanding how a program can detect inappropriate words. |
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4. Try changing the **sensitivity** (Strict / Balanced / Sensitive) to see how it affects the results. |
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This hands-on activity helps them connect basic coding logic (`if`, `elif`, `else`) with real-world AI behavior. |
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## Tech Used |
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- **Python 3.9+** |
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- **Streamlit** for the interactive web app |
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- **TextBlob** for simple sentiment polarity detection |
