Behavioral Precursor Parameters

Market Blade’s sentiment analysis hinges on a sophisticated model of group behavior, rooted in the concept of humans as state machines tasked with predicting and adapting to their environment. In trading, this translates to understanding collective actions reflected in market movements. The AI identifies 36 behavioral precursor parameters—granular indicators of psychological and social dynamics—derived from interdisciplinary research into storytelling patterns, dramatic situations, and affective neuroscience. These 36 parameters capture subtle precursors to group decision-making, such as:

• Cognitive Triggers: Indicators of attention (e.g., repetition of key terms), curiosity (e.g., question phrasing), or uncertainty (e.g., hedging language).

• Emotional Amplifiers: Markers of intensity (e.g., superlatives, exclamation), polarity (e.g., hope vs. fear), or contagion (e.g., retweet velocity).

• Social Signals: Measures of authority (e.g., citation index), alignment (e.g., echo chamber effects), or dissent (e.g., argument density).

Each sentiment is scored on a 0-50 scale, with temporal dynamics tracked to reveal wave-like patterns (see Section 3.3). The mapping from 36 precursors to 18 sentiments uses a principal component analysis (PCA) variant, optimized to preserve emotional contrast and predictive power.