Words of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning

TL;DR

This paper employs deep learning to analyze US presidential speeches, aiming to identify subtle rhetorical cues that may predict US involvement in major wars, blending machine learning with historical analysis.

Contribution

It introduces an interdisciplinary approach combining deep learning and historical inquiry to interpret presidential rhetoric related to war.

Findings

Neural networks can discern patterns in presidential speeches preceding wars.

Identifiable rhetorical features differentiate wartime from peacetime speeches.

The approach enhances interpretability of predictive models in political discourse.

Abstract

In political discourse and geopolitical analysis, national leaders words hold profound significance, often serving as harbingers of pivotal historical moments. From impassioned rallying cries to calls for caution, presidential speeches preceding major conflicts encapsulate the multifaceted dynamics of decision-making at the apex of governance. This project aims to use deep learning techniques to decode the subtle nuances and underlying patterns of US presidential rhetoric that may signal US involvement in major wars. While accurate classification is desirable, we seek to take a step further and identify discriminative features between the two classes (i.e. interpretable learning). Through an interdisciplinary fusion of machine learning and historical inquiry, we aspire to unearth insights into the predictive capacity of neural networks in discerning the preparatory rhetoric of US presidents preceding war. Indeed, as the venerable Prussian General and military theorist Carl von Clausewitz admonishes, War is not merely an act of policy but a true political instrument, a continuation of political intercourse carried on with other means (Clausewitz, 1832).