Could generative AI become a ghostwriter for the US president?

Abstract With ChatGPT, AI generative technology has demonstrated its ability to understand user queries and to write human-like messages. Recently, other large language models (LLMs) have gained significant momentum. Based on this technology, this study analyses the style and rhetoric of three LLMs by comparing the machine-generated speeches to those of recent US presidents. Specifically, it contrasts State of the Union addresses from Reagan to Biden with those produced by the GPT-3.5, GPT-4.0, and DeepSeek-v3 models. This analysis finds that LLM models frequently use the ‘we’ and produce shorter messages with, on average, longer sentences comprised of more complex words. Additionally, the computer-based models adopt a more optimistic tone and more often include terms related to political, symbolic, and abstract categories. Despite mimicking an author’s style, the generated speeches remain distinct from those of the original author. Finally, DeepSeek-v3 shows a closer similarity to those of the real US presidents.

Authors

Institutions

Publication Details

Journal
Journal of Language and Politics
Published
2025-09-19
DOI
https://doi.org/10.1075/jlp.24259.sav
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Could generative AI become a ghostwriter for the US president?

Jacques Savoy
Journal of Language and Politics
Authorship Attribution and Profiling
article

Could generative AI become a ghostwriter for the US president?

Jacques Savoy
article en

Abstract

Abstract With ChatGPT, AI generative technology has demonstrated its ability to understand user queries and to write human-like messages. Recently, other large language models (LLMs) have gained significant momentum. Based on this technology, this study analyses the style and rhetoric of three LLMs by comparing the machine-generated speeches to those of recent US presidents. Specifically, it contrasts State of the Union addresses from Reagan to Biden with those produced by the GPT-3.5, GPT-4.0, and DeepSeek-v3 models. This analysis finds that LLM models frequently use the ‘we’ and produce shorter messages with, on average, longer sentences comprised of more complex words. Additionally, the computer-based models adopt a more optimistic tone and more often include terms related to political, symbolic, and abstract categories. Despite mimicking an author’s style, the generated speeches remain distinct from those of the original author. Finally, DeepSeek-v3 shows a closer similarity to those of the real US presidents.

Journal of Language and Politics
University of Neuchâtel (CH)
Openalex Percentile: Top 87%
Authorship Attribution and Profiling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.