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

Zhong Tang; Stella Xin Yin; Dion Hoe Lian Goh

doi:10.1007/978-3-031-48044-7_25

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

Zhong Tang^*, Stella Xin Yin, Dion Hoe Lian Goh

^*Corresponding author for this work

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings
Editors	Hirohiko Mori, Yumi Asahi, Adela Coman, Simona Vasilache, Matthias Rauterberg
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	337-355
Number of pages	19
ISBN (Print)	9783031480430
DOIs	https://doi.org/10.1007/978-3-031-48044-7_25
Publication status	Published - 2023
Externally published	Yes
Event	25th International Conference on Human-Computer Interaction, HCII 2023 - Copenhagen, Denmark Duration: Jul 23 2023 → Jul 28 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14056 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th International Conference on Human-Computer Interaction, HCII 2023
Country/Territory	Denmark
City	Copenhagen
Period	7/23/23 → 7/28/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Keywords

Deepfakes
misinformation
news articles
sentiment analysis
topic analysis

Access to Document

10.1007/978-3-031-48044-7_25

Cite this

Tang, Z., Yin, S. X., & Goh, D. H. L. (2023). Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles. In H. Mori, Y. Asahi, A. Coman, S. Vasilache, & M. Rauterberg (Eds.), HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings (pp. 337-355). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14056 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-48044-7_25

Tang, Zhong ; Yin, Stella Xin ; Goh, Dion Hoe Lian. / Understanding Major Topics and Attitudes Toward Deepfakes : An Analysis of News Articles. HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings. editor / Hirohiko Mori ; Yumi Asahi ; Adela Coman ; Simona Vasilache ; Matthias Rauterberg. Springer Science and Business Media Deutschland GmbH, 2023. pp. 337-355 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles",

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{\textquoteright}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.",

keywords = "Deepfakes, misinformation, news articles, sentiment analysis, topic analysis",

author = "Zhong Tang and Yin, \{Stella Xin\} and Goh, \{Dion Hoe Lian\}",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 25th International Conference on Human-Computer Interaction, HCII 2023 ; Conference date: 23-07-2023 Through 28-07-2023",

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pages = "337--355",

editor = "Hirohiko Mori and Yumi Asahi and Adela Coman and Simona Vasilache and Matthias Rauterberg",

booktitle = "HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings",

address = "Germany",

}

Tang, Z, Yin, SX & Goh, DHL 2023, Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles. in H Mori, Y Asahi, A Coman, S Vasilache & M Rauterberg (eds), HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14056 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 337-355, 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, 7/23/23. https://doi.org/10.1007/978-3-031-48044-7_25

Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles. / Tang, Zhong; Yin, Stella Xin; Goh, Dion Hoe Lian.
HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings. ed. / Hirohiko Mori; Yumi Asahi; Adela Coman; Simona Vasilache; Matthias Rauterberg. Springer Science and Business Media Deutschland GmbH, 2023. p. 337-355 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14056 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Understanding Major Topics and Attitudes Toward Deepfakes

T2 - 25th International Conference on Human-Computer Interaction, HCII 2023

AU - Tang, Zhong

AU - Yin, Stella Xin

AU - Goh, Dion Hoe Lian

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings

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ER -

Tang Z, Yin SX, Goh DHL. Understanding Major Topics and Attitudes Toward Deepfakes: An Analysis of News Articles. In Mori H, Asahi Y, Coman A, Vasilache S, Rauterberg M, editors, HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 337-355. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-48044-7_25

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

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

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