Spaces:
Running
Running
license: mit | |
title: Social Aegis | |
sdk: gradio | |
emoji: ⚡ | |
colorFrom: blue | |
colorTo: yellow | |
pinned: true | |
sdk_version: 5.44.1 | |
# SocialAegis MVP | |
🛡️ A sentiment-based escalation engine to detect emotional volatility in social media posts. | |
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## Overview | |
SocialAegis is designed to analyze text from social media and other sources to detect sentiment, calculate a risk score, and determine whether escalation is needed. This helps organizations monitor emotional volatility in communications and take timely action. | |
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## Features | |
- **Sentiment Analysis** – Classifies input text as Positive, Neutral, or Negative. | |
- **Risk Scoring** – Provides a numerical score indicating the emotional intensity or risk level. | |
- **Escalation Trigger** – Indicates whether the text requires escalation based on the risk score. | |
- **Supports All Text Inputs** – Works with short posts, long messages, and multiple languages. | |
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## How to Use | |
1. Enter your text into the input box. | |
2. Click **Submit** or **Run**. | |
3. The app will return: | |
- **Sentiment** (Positive / Neutral / Negative) | |
- **Risk Score** (rounded to 2 decimal places) | |
- **Escalation Trigger** (Yes / No) | |
### Example Inputs | |
- `"I am so frustrated with this service!"` | |
- `"I had an amazing experience, thank you!"` | |
- `"This is unacceptable, I will report this."` | |
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## Dependencies | |
The app requires the following Python packages (all included in `requirements.txt`): | |
- `gradio` | |
- `transformers` | |
- `torch` | |
- `scipy` | |
- `sentencepiece` | |
- `protobuf` | |
- `langdetect` | |
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## Notes | |
- The model runs entirely in Hugging Face Spaces. No additional setup is required if you use the provided `requirements.txt`. | |
- For best results, enter text in a single language at a time. | |
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## Credits | |
Developed by Karthik Vinay for SocialAegis MVP. |