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

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.