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The public service media Radio Televisión Española (RTVE) conducted a proof-of-concept study to automatically generate reports on the results of the local elections of 28 May 2023 in Spanish communities with fewer than 1000 inhabitants. This study describes the creation, testing and application of the methodological tool used to evaluate the quality of the reports generated using artificial intelligence in order to optimize the algorithm. The application of the proposed datasheet provided a systematic analysis, and the iterative use of the tool made it possible to gradually improve the results produced by the system until a suitable threshold was reached for publication. The study also showed that, despite the ability of AI systems to automatically generate a large volume of information, both human labour and the reliability of the data that feed the system are essential to ensure journalistic quality. [ABSTRACT FROM AUTHOR]

This study aims to assess the persistence of traditional journalistic quality features within the contemporary digital ecosystem. Digital advancements have fundamentally altered media creation, notably with the emergence of artificial intelligence (AI) in newsrooms. AI holds potential for substantial shifts in journalism, impacting business models, dissemination methods, and professional practices. Present in 75% of newsrooms, AI streamlines tasks, allowing more creative time for journalists. Ethical and quality concerns persist, particularly regarding AI’s ability to meet journalism’s established quality standards. This article aims to investigate the incorporation of these quality criteria in news articles generated by artificial intelligence (AI). Focus group and in-depth interviews were used as methodological techniques, involving ten experts. It is concluded that journalistic ethics have remained intact despite the disruptive technological advances in recent decades. However, there is a need to integrate these ethics with new criteria associated with the tools being used. Therefore, it is necessary to consider criteria from a dual perspective: both social and technological. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Comunicación 'Vivat Academia' is the property of Facultad de Ciencias de las Informacion de la Universidad Complutense (Espana) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ISSN 2386-7876 - © 2021 Communication & Society, 34(2), 159-176 159 Artificial intelligence and journalism: Systematic review of scientific production in Web of Science and Scopus (2008-2019) Abstract Research about the use of Artificial Intelligence applied to journalism has increased over the years. Some concepts like robot journalism, algorithm journalism, automated journalism, computational journalism, augmented journalism, artificial journalism, high tech journalism or AI are used for the same purpose. In this same line, other specific studies in journalism (Martínez Nicolás, Saperas & Carrasco Campos, 2017), the mobile journalism (López et al., 2019), fake news (Blanco Alfonso, García Galera & Tejedor, 2019; Valero & Oliveira, 2018), transmedia narrative (Vicente Torrico, 2017), big data (Gindin, Busso & 2018), digital competencies in journalism (Marta-Lazo, Rodríguez & Peñalva, 2020) or the role of women in communication research (Martín Algarra, Serrano Puche & Rebollero, 2018) are noteworthy. The eleven most usual terms were: 1) "Computational journalism", present in 33% of scientific texts; 2) "Automated journalism", with 15.8%; 3) "Robot journalism", found in 15.3% of works; 4) "Journalism", appearing in 14.4% of production; 5) "Artificial intelligence", present in 13.9%; 6) "Data journalism", in 12.4%; 7) "Algorithms", used in 12%; 8) "Automation", found in 7.7% of researches; 9) "Algorithmic journalism", represented in 5.7%; 10) "Social media", found in 5.7% of the production and 11) "Big data", present in 5.3%. [Extracted from the article]

Copyright of Estudios sobre el Mensaje Periodistico is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Mediterranean Journal of Communication / Revista Mediterránea de Comunicación is the property of Revista Mediterranea de Comunicacion / Mediterranean Journal of Communication and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Prisma Social is the property of Revista Prisma Social and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In December 2019, Chinese authorities informed the World Health Organization about a new coronavirus disease that would come to be called Covid-19. The world media began reporting on this new virus and its consequences. However, reports about Covid-19 would not appear in the European and American media until their societies became aware of both the health and economic consequences of Covid-19 in March 2020. This article analyzes the online media coverage of economic inequality. The goal is to understand the formation of the public agenda, based on the impact of the disease on social classes as the main factor generating greater inequality levels, in particular inequality of opportunities as the most remarkable topic during the first stage of the pandemic. According to the first results of this content analysis, the social class divide will be deepened by the pandemic. For this study, a tool was designed to analyze both the manifest and latent content of the items. Using content analysis, an analysis of news published by 33 digital media in both Europe and Latin America from March 14 to April 14, 2020 was conducted. The results of this study show that income inequality appears as the core variable of the problem, although social classes remain important. The imbalanced access to health and education public services also receives continuous coverage in the media. However, poverty as a consequence of this situation remains an uncomfortable issue and tends to be presented in an undramatized way. [ABSTRACT FROM AUTHOR]

Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Doxa Comunicación is the property of Fundacion Universitaria San Pablo - CEU and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)