GPT as ghostwriter at the White House
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Abstract (arXiv)
Recently several large language models (LLMs) have demonstrated their capability to generate a message in response to a user request. Such scientific breakthroughs promote new perspectives but also some fears. The main focus of this study is to analyze the written style of one LLM called ChatGPT 3.5 by comparing its generated messages with those of the recent US presidents. To achieve this objective, we compare the State of the Union addresses written by Reagan to Obama with those automatically produced by ChatGPT. We found that ChatGPT tends to overuse the lemma "we" as well as nouns and commas. On the other hand, the generated speeches employ less verbs and include, in mean, longer sentences. Even when imposing a given style to ChatGPT, the resulting speech remains distinct from messages written by the target author. Moreover, ChatGPT opts for a neutral tone with mainly positive emotional expressions and symbolic terms (e.g., freedom, nation). Finally, we show that the GPT's style exposes distinct features compared to real presidential addresses.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 30 references that are in the map. First posted on arXiv 27 Nov 2024.
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6 of 30 references.
References · 6
- 2017Attention Is All You Needcited by 59,932
- 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
- 2023A Survey of Large Language Modelscited by 2,537
- 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
- 2023Is ChatGPT A Good Translator? Yes With GPT-4 As The Enginecited by 172
- 2023Towards a Robust Detection of Language Model Generated Text: Is ChatGPT that Easy to Detect?cited by 23
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