AI in the Newsroom: Analyzing the Increase in ChatGPT-Favored Words in News Articles
Aayush Kucheria, Okko Katajamäki, Santeri Koivula, Andrea La Mantia, Norman Piotrowski · Team Aalto EA
Submitted to AI and Democracy Hackathon: Demonstrating the Risks. Sprint projects are early-stage work by participants, not Apart Research publications.
Media plays a vital role in informing the public and upholding accountability in democracy. However, recent trends indicate declining trust in media, and there are increasing concerns that artificial intelligence might exacerbate this through the proliferation of inauthentic content. We investigate the usage of large language models (LLMs) in news articles, analyzing the frequency of words commonly associated with ChatGPT-generated content from a dataset of 75,000 articles. Our findings reveal a significant increase in the occurrence of words favored by ChatGPT after the release of the model, while control words saw minimal changes. This suggests a rise in AI-generated content in journalism.
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@misc{kucheria2024ai,
title = {{AI in the Newsroom: Analyzing the Increase in ChatGPT-Favored Words in News Articles}},
author = {Aayush Kucheria and Okko Katajamäki and Santeri Koivula and Andrea La Mantia and Norman Piotrowski},
year = {2024},
month = may,
note = {Submitted to AI and Democracy Hackathon: Demonstrating the Risks, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/ai-in-the-newsroom-analyzing-the-increase-in-chatgpt-favored-words-in-news-articles}},
url = {https://apartresearch.com/sprints/projects/ai-in-the-newsroom-analyzing-the-increase-in-chatgpt-favored-words-in-news-articles}
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