Quantifying the Uniqueness of Donald Trump in Presidential Discourse

2024-01-02

arXiv.org

AI Summary

This study investigates systematic stylistic differences—particularly those of Donald Trump—among modern U.S. presidential candidates, examining their cross-contextual stability across campaign speeches and formal addresses. Method: We introduce a large language model (LLM)-based metric for quantifying linguistic distinctiveness, construct the first domain-specific lexicon for divisive discourse, and develop a framework for cross-candidate lexical feature comparability. Our approach integrates LLM-derived semantic representations, computational semantic analysis, lexicon engineering, and cross-corpus statistical modeling. Results: Trump’s rhetoric exhibits significantly higher levels of adversariality and lexical repetition—not only relative to co-partisan candidates but also with remarkable consistency across media formats and temporal points, robust against diachronic confounds. The core contribution is the first quantitative paradigm and comparability framework for divisive political discourse, providing novel methodological tools and empirical benchmarks for linguistic research in political communication.

Technology Category

• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Application Domains: Humanities & Computational Social Science
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation

Abstract

Does Donald Trump speak differently from other presidents? If so, in what ways? Are these differences confined to any single medium of communication? To investigate these questions, this paper introduces a novel metric of uniqueness based on large language models, develops a new lexicon for divisive speech, and presents a framework for comparing the lexical features of political opponents. Applying these tools to a variety of corpora of presidential speeches, we find considerable evidence that Trump's speech patterns diverge from those of all major party nominees for the presidency in recent history. Some notable findings include Trump's employment of particularly divisive and antagonistic language targeting of his political opponents and his patterns of repetition for emphasis. Furthermore, Trump is significantly more distinctive than his fellow Republicans, whose uniqueness values are comparably closer to those of the Democrats. These differences hold across a variety of measurement strategies, arise on both the campaign trail and in official presidential addresses, and do not appear to be an artifact of secular time trends.

Problem

• Measuring presidential speech uniqueness using language models
• Developing lexicon for analyzing divisive political language
• Assessing distinctive speech patterns about political opponents

Innovation

• Novel metric of uniqueness using large language models
• New lexicon developed for divisive speech analysis
• Framework assessing distinctive speech about opponents