Artificial Intelligence as an Opportunity for Journalism: Insights from the Brazilian and Portuguese Media

João Canavilhas (), Fabia Ioscote and Adriana Gonçalves
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João Canavilhas: Faculty of Arts and Letters, University of Beira Interior, 6201-001 Covilhã, Portugal
Fabia Ioscote: Arts, Communication and Design Sector, Federal University of Paraná, Curitiba 81531-990, Brazil
Adriana Gonçalves: Faculty of Arts and Letters, University of Beira Interior, 6201-001 Covilhã, Portugal

Social Sciences, 2024, vol. 13, issue 11, 1-15

Abstract: Artificial Intelligence (AI) has been emerging as a topic of significant interest, attracting the attention of the public and leading to an increase in research and on media coverage of this technology. This article examines how the Brazilian and Portuguese media represent AI in journalism and the challenges it poses. Using digital methods, this study analysed 60 news articles published between June 2022 and June 2024. The data were collected through an anonymous search on Google News, and the content was analysed using sentiment analysis with the PTNews software, followed by a similarity analysis using the Iramuteq software. The results show a predominantly positive sentiment towards AI in journalism, with 91.8% of articles highlighting its benefits, such as increased efficiency and the automation of routine tasks. However, concerns about disinformation, ethical implications, and the potential erosion of journalistic credibility were less emphasised. The analysis also identified key themes, including AI’s dual role as both an enabler and a threat to journalism, the importance of human oversight, and the challenges of newsroom adaptation. The findings suggest that the Brazilian and Portuguese media generally present AI as an opportunity for journalism, often downplaying the associated risks and ethical challenges.

Keywords: artificial intelligence; digital methods; journalism; media coverage; sentiment analysis (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2024
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