NDLI: Exploring audience perceptions of, and preferences for, data-driven ‘quantitative’ journalism

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Exploring audience perceptions of, and preferences for, data-driven ‘quantitative’ journalism

Content Provider	SAGE Publishing
Author	Stalph, Florian Thurman, Neil Thäsler-Kordonouri, Sina
Copyright Year	2023
Abstract	Although data-driven ‘quantitative' journalism has increased in volume and visibility, little is known about how it is perceived and evaluated by audiences. This study helps fill this research gap by analysing the characteristics of quantitative journalism that a diverse group of 31 news consumers pay attention to and, within those characteristics, where their preferences might lie. In eight group interviews, participants read and discussed articles chosen to represent the diversity that exists in the forms and production of data-driven journalism. Our analysis reveals 28 perception criteria that we group into four major categories: antecedents of perception, emotional and cognitive impacts, article composition, and news and editorial values. Several criteria have not been used in prior research on the perception of quantitative journalism. Our criteria have obvious application in future research on how audiences perceive different types of quantitative journalism, including that produced with the help of automation. The criteria will be of interest too for researchers studying audience perceptions and evaluations of news in general. For journalists and others communicating with numbers, our findings indicate what audiences might want from data-driven journalism, including that it is constructive, concise, provides analysis, has a human angle, and includes visual elements.
Related Links	https://journals.sagepub.com/doi/pdf/10.1177/14648849231179606?download=true
ISSN	14648849
Journal	Journalism (JOU)
e-ISSN	17413001
DOI	10.1177/14648849231179606
Language	English
Publisher	Sage Publications UK
Publisher Date	2023-06-07
Publisher Place	London
Access Restriction	Open
Rights Holder	© The Author(s) 2023
Subject Keyword	data journalism quantitative journalism automated journalism audience studies news credibility artificial intelligence group interviews news quality news perception News perception criteria
Content Type	Text
Resource Type	Article
Subject	Arts and Humanities Communication

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