Multimodal AI-based visualization of strategic leaders' emotional dynamics: a deep behavioral analysis of Trump's trade war discourse
Wei Meng

TL;DR
This paper presents a multimodal AI framework analyzing Trump's emotional and behavioral dynamics during trade negotiations, revealing non-rational decision patterns and proposing a strategic intervention model.
Contribution
It introduces a novel multimodal cognitive-behavioral modeling approach to analyze political leaders' emotional rhythms and decision-making processes.
Findings
Trump's decisions are driven by dominance-coherence rhythms.
The framework captures micro-expressions, acoustic cues, and semantic flow.
A six-axis strategic tempo intervention framework is proposed.
Abstract
This study investigates the emotional rhythms and behavioral mechanisms of dominant political leaders in strategic decision-making. Using the Trump administration's 125 percent tariff hike on China as a case, it adopts a Multimodal Cognitive Behavioral Modeling framework. This includes micro-expression tracking, acoustic intonation analysis, semantic flow modeling, cognitive load simulation, and strategic behavior mapping to construct a full-cycle simulation of emotion, motivation, and output. Results reveal that Trump's decisions are not driven by rational deduction, but emerge from dominance-coherence rhythms. A six-axis National Strategic Tempo Intervention Framework is proposed to support anticipatory policy modeling.
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Taxonomy
TopicsAction Observation and Synchronization · Cognitive Science and Mapping · Language, Metaphor, and Cognition
