A2 Review article, Literature review, Systematic review
Mapping Automation in Journalism Studies 2010–2019 : A Literature Review (2024)

Siitonen, M., Laajalahti, A., & Venäläinen, P. (2024). Mapping Automation in Journalism Studies 2010–2019 : A Literature Review. Journalism Studies, 25(3), 299-318. https://doi.org/10.1080/1461670x.2023.2296034

JYU authors or editors

Publication details

All authors or editors: Siitonen, Marko; Laajalahti, Anne; Venäläinen, Päivi

Journal or series: Journalism Studies

ISSN: 1461-670X

eISSN: 1469-9699

Publication year: 2024

Publication date: 27/12/2023

Volume: 25

Issue number: 3

Pages range: 299-318

Publisher: Routledge

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1080/1461670x.2023.2296034

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/92608

Abstract

The algorithmic turn has fundamentally transformed journalistic work. Academic interest in the implication of automated algorithms for journalism has grown hand-in-hand with their everyday use. This paper presents a literature review of peer-reviewed research reports (N = 62) on automated algorithms in the context of journalistic work. Our review focuses on the first decade (2010–2019) during which automated journalism gained traction. The study identifies the most prominent perspectives or themes that studies in automated journalism have explored and the future directions for research that researchers have proposed. Based on the analysis, the dominant themes that studies in automated journalism have covered include (1) testing and developing algorithmic tools, (2) developing practices and policies for journalistic work, (3) attitudes and technology acceptance, and (4) societal and macro-level discourses concerning AI and journalism. The new directions for research that studies on automated algorithms have recognized relate to (1) target groups and stakeholders—that is, who to study in the future; (2) emergent themes and phenomena—that is, what to study in the future; and (3) approaches and methodologies—that is, how to study these topics in the future. These findings help create a holistic picture of possible future directions for the field.

Keywords: journalism; online journalism; algorithms; artificial intelligence

Free keywords: algorithmic journalism; artificial intelligence; automated algorithms; automated journalism; computational journalism; robot journalism

Contributing organizations

Ministry reporting: Yes

VIRTA submission year: 2023

JUFO rating: 3