Automation in Sports Reporting: Strategies of Data Providers, Software Providers, and Media Outlets

Abstract

<jats:p>This study examines how algorithmic processing affects structures and practices in sports journalism in Germany. A multi-level perspective is used to determine which strategies data providers, software providers, and media outlets use to develop automated reporting, which compiles perspectives across the entire line of news production. The results of 11 in-depth interviews show that non-journalistic actors are vital partners in the news production process, as all actors work together in data handling, training, and software development. Moreover, automation can generate additional content such as match and historical coverage to help address shortfalls in capacity. However, given the business case for automation, amateur football (soccer) is currently the only viable candidate for its use. Many actors involved in the process argue that automated content is an added value for their readers, but claim that content quality has to be put before quantity. This means that some media outlets edit automated articles to increase the quality of their sports journalism, but that this is done only on a small scale. Media outlets do not perceive their roles to be changing, but see automation as a helpful tool that complements their work; a few use automatically created articles as a baseline for in-depth reporting. Moreover, the so-called ‘meta-writer’ has not become a reality yet, as data-processing and news writing are still kept separate. This article sheds new light on the use of automation in the sports beat, highlighting the growing role of non-journalistic actors in the news production process.</jats:p>

Literature Review on Artificial Intelligence in Journalism: A Bibliometric Analysis of Publications Indexed in the Web of Science and Scopus

“…Scholars several terms concerning the field of AI in journalism: "robot journalism", "automated journalism", "algorithmic journalism" and "automated news". Kunert [5], Moravec et al [6], Segarra-Saavedra et al [7], Milosavljevic et al [8] apply the term "automated journalism" to AI in the media, arguing that this is the most usable tool for journalists. Brlek et al [9], Diakopoulos et al [10], Dorr et al [11], Waddel [12] propose "algorithmic journalism" emphasizing that AI is used to gather information and produce stories.…”

At the crossroads of logics: Automating newswork with artificial intelligence—(Re)defining journalistic logics from the perspective of technologists

“…Some companies offer users the option to modify the content and look of the generated text, or use it as a baseline for further editing, whereas other systems publish stories directly. Certain providers aid news organizations in locating data sources (Kunert, 2020), yet responsibility for data accuracy and output errors is most often placed with the data providers and publishers.…”

“…1108, 1110). AI solutions can also have cascade effects: moving reporters from writing to data management and editing automated stories for clarity and context, and overriding the need for traditional news outlets by providing direct access to automated content, especially in the case of sports news (Kunert, 2020).…”

Periodismo digital y alta tecnología: de la consolidación a los renovados desafíos

“…Los estudios encontrados abordan cuestiones relativas, entre otras, a los cambios y transformaciones que la automatización de funciones ha producido en las redacciones en particular (Wu, Tandoc y Salmon, 2019a) y en el periodismo en general (Wu, Tandoc y Salmon, 2019b); a la percepción de los usuarios de la credibilidad, calidad y/u objetividad de las noticias automatizadas (Graefe y Bohlken, 2020;Liu y Wei, 2019;Tandoc, Yao y Wu, 2020;Waddell, 2019aWaddell, , 2019b; a la calidad de las piezas redactadas por una inteligencia artificial (Ufarte y Manfredi, 2019); a la responsabilidad jurídica del contenido cuando este ha sido escrito por un bot o algoritmo (Lewis, Sanders y Carmody, 2019); a la automatización en las coberturas deportivas (Kunert, 2020;Rojas, 2019;Rojas y Toural, 2019); al impacto del uso de bots en la relación del medio con la audiencia (Ford y Hutchinson, 2019;Jones y Jones, 2019); al periodismo estructurado (Caswell, 2019); o a los retos y riesgos de la personalización de contenidos (Kunert y Thurman, 2019). De la Peña et al (2010: 291) definieron por primera vez el periodismo inmersivo como «la producción de noticias de forma que la gente pueda obtener una experiencia en primera persona de los eventos o situaciones descritas en los relatos informativos».…”