Artificial Intelligence in the Spotlight: A Study of Brazilian News Coverage
Abstract
Artificial Intelligence (AI) has become increasingly integrated into different layers of society, bringing both benefits and risks. With the growth of this technology, media coverage of it has also intensified. This paper analyzes media coverage of AI in Brazil, identifying the predominant themes and trends in news about the technology. To this end, four news portals were analyzed using topic modeling. The results show that the news addresses the impact of AI on the job market, advances in health, political issues involving regulation and disinformation, and technological innovations. Therefore, the study provides a comprehensive view of the topics highlighted by the media on the main Brazilian portals, contributing to the state of the art by promoting insights that can serve as a basis for the formulation of public policies and regulations regarding the technology.
Keywords:
Artificial Intelligence, Media coverage, Text mining
References
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Stroparo, T. R., de Araújo, J. H. K., Bortolotti, M. A., and Junior, O. d. S. L. (2024). Inteligência artificial na gestão de custos: avanços, desafios e oportunidades. Revista Ibero-Americana de Humanidades, Ciências e Educação, 10(6):1446–1456.
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Baines, R. L. and Regan de Bere, S. (2018). Optimizing patient and public involvement (ppi): Identifying its “essential” and “desirable” principles using a systematic review and modified delphi methodology. Health Expectations, 21(1):327–335.
Baumer, E. P., Mimno, D., Guha, S., Quan, E., and Gay, G. K. (2017). Comparing grounded theory and topic modeling: Extreme divergence or unlikely convergence? Journal of the Association for Information Science and Technology, 68(6):1397–1410.
Belli, L., Curzi, Y., and Gaspar, W. B. (2023). Ai regulation in brazil: Advancements, flows, and need to learn from the data protection experience. Computer Law & Security Review, 48:105767.
Bunz, M. and Braghieri, M. (2022). The ai doctor will see you now: assessing the framing of ai in news coverage. AI & society, 37(1):9–22.
Choi, S. (2024). Temporal framing in balanced news coverage of artificial intelligence and public attitudes. Mass Communication and Society, 27(2):384–405.
Chuan, C.-H. (2023). A critical review of news framing of artificial intelligence. Hand-book of Critical Studies of Artificial Intelligence, pages 266–276.
Cools, H., Van Gorp, B., and Opgenhaffen, M. (2024). Where exactly between utopia and dystopia? a framing analysis of ai and automation in us newspapers. Journalism, 25(1):3–21.
Costa, G. d. S., Couto, D. C., Junior, A. F. J., and Lobato, F. M. (2022). Feminismo e redes sociais online: uma análise de tweets sobre o dia internacional da mulher. In Anais do XI Brazilian Workshop on Social Network Analysis and Mining, pages 169–180. SBC.
Egger, R. and Yu, J. (2022). A topic modeling comparison between lda, nmf, top2vec, and bertopic to demystify twitter posts. Frontiers in sociology, 7:886498.
Garcia, A. C. (2020). Ética e inteligencia artificial. Computação Brasil, (43):14–22.
George, A. S., George, A. H., and Martin, A. G. (2023). Chatgpt and the future of work: a comprehensive analysis of ai’s impact on jobs and employment. Partners Universal International Innovation Journal, 1(3):154–186.
Grootendorst, M. (2022). Bertopic: Neural topic modeling with a class-based tf-idf procedure. arXiv preprint arXiv:2203.05794.
Longoni, C., Fradkin, A., Cian, L., and Pennycook, G. (2022). News from generative artificial intelligence is believed less. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, pages 97–106.
Maedche, A., Legner, C., Benlian, A., Berger, B., Gimpel, H., Hess, T., Hinz, O., Morana, S., and Söllner, M. (2019). Ai-based digital assistants: Opportunities, threats, and research perspectives. Business & Information Systems Engineering, 61:535–544.
Marques, F. P. J., Miola, E., Mitozo, I., and Mont’Alverne, C. (2020). Similar, but not the same: Comparing editorial and news agendas in brazilian newspapers. Journalism Practice, 14(9):1066–1086.
Mohamed, A. A. and Lucke-Wold, B. (2024). Apple intelligence in neurosurgery. Neurosurgical Review, 47(1):327.
Molina, A. C. and Berenguel, O. L. (2022). Deepfake: A evolução das fake news. Research, Society and Development, 11(6):e56211629533–e56211629533.
Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M.-E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., et al. (2020). Bias in data-driven artificial intelligence systems—an introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3):e1356.
Ouchchy, L., Coin, A., and Dubljević, V. (2020). Ai in the headlines: the portrayal of the ethical issues of artificial intelligence in the media. AI & SOCIETY, 35:927–936.
Peña-Fernández, S., Meso-Ayerdi, K., Larrondo-Ureta, A., and Díaz-Noci, J. (2023). Without journalists, there is no journalism: the social dimension of generative artificial intelligence in the media. El Profesional de la información, 32(2).
Ralph, P. and Baltes, S. (2022). Paving the way for mature secondary research: the seven types of literature review. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pages 1632–1636.
Schneider, J., Seidel, S., Basalla, M., and vom Brocke, J. (2023). Reuse, reduce, support: Design principles for green data mining. Business & Information Systems Engineering, 65(1):65–83.
Siegle, D. (2023). A role for chatgpt and ai in gifted education. Gifted Child Today, 46(3):211–219.
Spatola, N. and Urbanska, K. (2020). God-like robots: the semantic overlap between representation of divine and artificial entities. Ai & Society, 35(2):329–341.
Stroparo, T. R., de Araújo, J. H. K., Bortolotti, M. A., and Junior, O. d. S. L. (2024). Inteligência artificial na gestão de custos: avanços, desafios e oportunidades. Revista Ibero-Americana de Humanidades, Ciências e Educação, 10(6):1446–1456.
Sun, S., Zhai, Y., Shen, B., and Chen, Y. (2020). Newspaper coverage of artificial intelligence: A perspective of emerging technologies. Telematics and Informatics, 53:101433.
Wirth, R. and Hipp, J. (2000). Crisp-dm: Towards a standard process model for data mining. In Proceedings of the 4th international conference on the practical applications of knowledge discovery and data mining, volume 1, pages 29–39. Manchester.
Published
2024-11-17
How to Cite
FERNANDEZ, Jonathan Oliveira; PONTES, Andrey Silva; REZENDE, Solange Oliveira; LOBATO, Fábio Manoel França.
Artificial Intelligence in the Spotlight: A Study of Brazilian News Coverage. In: NATIONAL MEETING ON ARTIFICIAL AND COMPUTATIONAL INTELLIGENCE (ENIAC), 21. , 2024, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 858-869.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2024.245256.
