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Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles

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HCI International 2023 – Late Breaking Papers (HCII 2023)

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Abstract

Deepfakes, highly realistic fake videos or images created using deep learning algorithms, have raised concerns due to their potential for malicious use and the dissemination of false information. This paper aims to analyze news articles related to deepfakes, focusing on the major topics discussed and the attitudes expressed toward this emerging technology. Understanding the public’s awareness, concerns, and reactions toward deepfakes is crucial in shaping informed responses. This study conducted exploratory data analysis, topic modeling analysis, and sentiment analysis by examining 4,920 news articles from the Nexis Uni database between 2000 and 2022. The topics discussed encompass various domains, including politics, business, entertainment, and more. We uncovered how deepfakes can be used for manipulation, the risks they pose to industries, and their potential impact on public trust and society. Furthermore, sentiment analysis of the news articles allowed us to gauge the overall public perception of deepfakes. We examined the emotional tone and attitudes conveyed in the articles to determine whether deepfakes were portrayed as a threat, a tool for mischief, or a harmless form of entertainment. This analysis provides insights into the prevailing sentiments surrounding deepfakes and their potential implications. This study addresses the research gap on the evolution of deepfake topics and sentiments over time and across diverse contexts.

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Acknowledgements

We would like to acknowledge the financial support provided by the Ministry of Education (Singapore) through the Tier 2 grant (MOE-T2EP40122–0004).

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Correspondence to Zhong Tang .

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Tang, Z., Yin, S.X., Goh, D.HL. (2023). Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles. In: Mori, H., Asahi, Y., Coman, A., Vasilache, S., Rauterberg, M. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14056. Springer, Cham. https://doi.org/10.1007/978-3-031-48044-7_25

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  • DOI: https://doi.org/10.1007/978-3-031-48044-7_25

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