How Amaalsense Works
From raw text to emotional insights - discover our revolutionary Hybrid Engine that combines proprietary formulas with AI.
Our unique approach combines the best of both worlds
Proprietary Mathematical Formula
Based on DCFT (Digital Collective Field Theory) - a unique methodology developed specifically for collective emotion analysis.
Advanced AI Analysis
Leverages state-of-the-art language models for nuanced sentiment understanding across Arabic and English content.
The 6-Step Process
We gather text data from 8 diverse sources: news agencies, social media platforms, video platforms, and messaging channels - in both Arabic and English.
Our unique Hybrid Engine combines proprietary mathematical formulas (70%) with advanced AI analysis (30%) for unprecedented accuracy in emotion detection.
Each text is converted into 6 emotional dimensions: Joy, Fear, Anger, Sadness, Hope, and Curiosity - creating a complete emotional fingerprint.
Emotional vectors are aggregated using our proprietary DCFT methodology to calculate three core indices: GMI (Global Mood), CFI (Fear), and HRI (Hope).
Data is organized by country and region, creating a real-time emotional map of the world with color-coded indicators and city-level analysis.
Our system monitors for sudden changes in emotional indices, triggering Telegram alerts when significant shifts are detected.
The 6 Emotional Vectors
Joy
Happiness, excitement, pleasure
Fear
Anxiety, worry, concern
Anger
Frustration, outrage, irritation
Sadness
Grief, disappointment, sorrow
Hope
Optimism, anticipation, faith
Curiosity
Interest, wonder, inquiry