🧠💭 Emotion Knowledge Graph

"Ἡ Μήδεια τὰ πάθη διὰ νοῦ εἰς δίκτυα συνείρει"
"Medea weaves emotions through intelligence into networks"

Analyze emotional content with LLM-powered extraction and sentiment-based visualization.
All emotions supported - including negative ones like disgust, hatred, contempt, and rage.

🎭 Emotion Analysis Configuration

🔍 Analysis Mode

🤖 AI Model Selection
Current Priority: Gemini → OpenAI → Anthropic
Available Models: 7 models across 3 providers

🌍 Text Language

Auto-detect analyzes Unicode characters. Override if needed.

📊 Visualization Style

😈 Emotion Types

Include Negative Emotions (disgust, hatred, etc.)

🔮 Enhanced Analysis (Cairns Framework)

Enable Script-Based Analysis
Extracts full emotion scripts, prototypicality scores, cultural context (honor/shame), and alternative interpretations
Minimum 10 characters. Include descriptive emotional language for best results.

💀 Emotion Analysis Failed

🧠 Emotion Analysis Results

Overall Sentiment:
0.0
0
Total Emotions
-
Dominant Emotion
0%
Positive
0%
Negative
Node Colors (Sentiment)
Very Positive (0.5 to 1.0)
Positive (0.1 to 0.5)
Neutral (-0.1 to 0.1)
Negative (-0.5 to -0.1)
Very Negative (-1.0 to -0.5)
Node Sizes
Size = Emotion Intensity
Larger nodes = stronger emotions
Border Colors (Type)
Primary Emotion
Complex Emotion
Mood

🧠 Analyzing Emotions

The Oracle is analyzing emotional content and mapping sentiment networks...