Research Evolution and Hotspots Analysis of Disinformation Induced by Generative Artificial Intelligence (2020–2025)

Main Article Content

Hancheng Zheng
School of Economics & Management, Nanjing Tech University, Nanjing 210000, China

DOI: https://doi.org/10.70267/cai.26v3n3.258270

Keywords

generative artificial intelligence, disinformation, deepfake, large language models, bibliometrics, network analysis

Abstract

The ubiquitous integration of social media in our day to day life has one inevitable consequence, namely the serious threat of artificial intelligence (AI)-produced fake news and misinformation. Generative models can nowadays generate natural looking text with high quality. They are used in many different settings, and the consequences affect everyone which from individual users up through organizations, institutions, and societies. Monitoring where that research is going is not just an academic exercise, which requires identifying real hotspots. The data set for this analysis consists of 571 papers in English published by the Web of Science Core Collection, exclusively in 2020-2025 period. Multidimensional quantitative data of the literature analysis are acquired by CiteSpace and VOSviewer. It can be seen that there is a significant increase in publication after 2023. Currently, the United States and China are dominant in world production. Oddly enough, while overall macro-level productivity is high, institutions barely collaborate with each other at the micro-level. The thematic focus has shifted. The earlier works were largely chasing computer vision tasks such as detecting deepfakes; today’s literature is heavy on controlling multimodal disinformation generated by LLMs. This trend is already seeping into risky domains, especially health care and journalism. Even with the emergence of new trends, fundamental knowledge here still resides on generative adversarial networks, residual networks, and preliminary deepfake evaluations. Finally, our study provides insight into the landscape of what is known within the discipline. Policy makers and scientists have a data-driven reference point from which to identify gaps in research and design policies that truly integrate science.

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Published
Jul 22, 2026
Issue
Vol. 3 No. 3 (2026)
Section
Research Articles
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How to Cite

Zheng, H. . (2026). Research Evolution and Hotspots Analysis of Disinformation Induced by Generative Artificial Intelligence (2020–2025). Computers and Artificial Intelligence, 3(3), 258-270. https://doi.org/10.70267/cai.26v3n3.258270