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

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.

Understanding and Enhancing Journalism Students’ Perception of Data Journalism

“…In the past decade, the landscape of academic research in data journalism has experienced a notable increase in collaborative endeavors across journalism, computer science and data science, resulting in a substantial body of studies delving into the intricacies of data journalism practices. Encompassing a range of research topics, such as tools and technologies, ethical considerations, education and training, audience engagement and the impact on traditional newsrooms, this growing body of work has identified key challenges, including issues related to data quality, access and ongoing training (Appelgren and Nygren 2014;Karlsen and Stavelin 2014;De Maeyer et al 2015;McBride 2016;Borges-Rey 2016;Cushion et al 2017;Stalph 2018;Appelgren and Salaverría 2018;Appelgren 2019;Heravi 2019;Usher 2020;Vanacker 2021;Tong and Zuo 2021;Fahmy and Attia 2021;Arias-Robles and López 2021;Jamil 2021;Martin et al 2022;de-Lima-Santos 2022;Haim 2022;Zhang and Chen 2022;Bhaskaran et al 2022;Guan and Wang 2022;Heravi et al 2022;Bisiani et al 2023;Stalph et al 2023;Chaparro-Domínguez and Díaz-Campo 2023;de-Lima-Santos and Mesquita 2023;Wu 2023;Ramsälv et al 2023).…”

“…Data journalism is open to collaboration among other specialties in the newsrooms, such as programmers and designers (Sandoval-Martín and La-Rosa 2018; Veglis et al 2022), and open to interpretation by the audience, since the projects can be consumed by individuals with a variety of perception criteria, at their personal paces and comprehension levels (Stalph et al 2023). Data journalists, to reach their audiences, create various data journalism formats and interactivity forms, while preserving their role as gatekeepers of information (Anderson and Borges-Rey 2019).…”

Répétitions et variations des textes générés

“…Dans le cadre des sciences de la communication et des médias, les textes générés sont étudiés en les comparant à des textes similaires rédigés par des journalistes en chair et en os (cf. Jung et al 2017;Graefe et al 2018 ;Stalph, Thaesler-Kordonouri & Thurman 2021 ainsi que la bibliographie citée par Thurman 2019: 185 et Dierickx 2021.…”