With nearly 70 million monthly ChatGPT users in the U.S., large language models and chatbots are now used for everyday activities, corporate campaigns, research methods and more. However, even with this rapid expansion, how large language models are trained and why they respond to prompts the way they do remains unclear.

A team of two Florida State University researchers, a computational linguist and a philosopher of science, is launching a novel research area to investigate why ChatGPT responds the way it does. Their study, “Why Does ChatGPT ‘Delve’ So Much? Exploring the Source of Overrepresentation in Large Language Models,” was published in the Proceedings of the 31st International Conference on Computational Linguistics in January and is the first scientific evidence pointing toward why ChatGPT tends to overuse certain words.

“We were inspired to conduct this study after seeing discussions online from scholars who noticed different abstracts overusing very specific words,” said Zina Ward, assistant professor in the Department of Philosophy and Interdisciplinary Data Science Master’s Degree Program faculty. “In addition to determining which words were being overused by ChatGPT, our research sought to understand how this overuse comes about. These language models are so new that there’s not much other research looking at their use of language.”

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