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

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.

arXiv commentIt integrates artificial intelligence, multimodal cognitive modeling, political behavior simulation, and data visualization, making it an interdisciplinary AI-based modeling study