Digital Journalism

Cloudy, Joshua; Banks, Jaime; Bowman, Nicholas David

doi: 10.1080/21670811.2021.1969974pmid: N/A

Abstract In the face of increasing public distrust for journalistic institutions, stories sourced from artificially intelligent (AI) journalists have the potential to lower hostile media bias by activating the machine heuristic—a mental shortcut assuming machines are more unbiased, systematic, and accurate than are humans. An online experiment targeting issue partisans found support for the prediction: a story presented as sourced from an AI journalist activated the machine heuristic that, in turn, mitigated hostile media bias. This mediation effect was moderated: perceived bias was more strongly reduced as partisan-attitude extremity increased.

Makhortykh, Mykola; Wijermars, Mariëlle

doi: 10.1080/21670811.2021.1970601pmid: N/A

Abstract The increasing use of recommender systems to provide personalized news delivery influences media systems worldwide. Using different data sources to predict what content will be interesting for specific readers, recommender systems can better accommodate individual information needs, but also raise concerns about potential audience fragmentation. However, current assessments of the effects of news personalization are predominantly based on observations from Western democracies. This Western-centric approach raises concerns about these assessments’ applicability to other contexts, in particular non-democratic ones, and brings to question the influence of prevalent Western conceptualisations of news personalization (e.g., filter bubbles) on attitudes towards it in non-Western countries. To address this gap, we scrutinize discussions of the promises and threats of news personalization in countries characterized by limited press freedom: Belarus, Russia and Ukraine. Using document analysis, we examine how three categories of actors—academics, journalists and IT specialists—discuss news personalization and the ways it can affect the public sphere. Through our analysis we uncover how Western conceptualisations of news personalization interact with discussions about it in non-democratic media systems and scrutinize whether existing concerns about personalization are applicable to non-Western contexts.

Stenbom, Agnes; Wiggberg, Mattias; Norlund, Tobias

doi: 10.1080/21670811.2021.2007781pmid: N/A

Abstract This article contributes to the emerging field of research on computational journalism with a practical illustration of an attempt to utilize Machine Learning to generate Search Engine Optimized headlines in a major Swedish newsroom. By using its technical results as a springboard for reflections among internal stakeholders, the experiment serves as a catalyzing innovation revealing deliberations on computational approaches in journalism in general and communicative Artificial Intelligence (AI) in specific. The study concludes with three ideas to support decision makers involved in evaluating potential use cases for communicative AI in journalism.

Stalph, Florian; Heravi, Bahareh

doi: 10.1080/21670811.2021.1957965pmid: N/A

Abstract This study introduces a synthesised framework for the analysis of data visualisations in the news. Through a close examination of seminal content analyses, their methodologies and findings, this article proposes a framework that consolidates dimensional components of data visualisations previously scattered across this body of research. To transition from incidental and essentialist examinations of visual data artefacts towards a systematic and theory-informed exploration, we consider the diagrammatic dimensions of data visualisations. The offered synthesized framework can serve as a starting point for both theory-infused descriptive purposes as well as more theory-guided explorations. The framework is put to the test by analysing 185 visualisations drawn from award-winning data stories. Findings generated through the application of the framework highlight the varied composition of components of data visualisations, though certain combinations of components are prevalent, leading to static categorical comparisons or interactive spatial localization. After all, data artefacts can be understood as problem-posing elements that are the outcome of diagrammatic thinking that journalists employ to communicate claims.

Wright, Scott; Nolan, David

doi: 10.1080/21670811.2021.1927779pmid: N/A

Abstract Using semi-structured interviews with Chinese data journalists across party and commercial media, this article assesses the structure and practice of data journalism in China. In doing this, it responds to calls for further studies of data journalism in non-western contexts. It finds that Chinese data journalists face some of the same pressures and challenges that have been documented in other countries, including limited access to data and the constraints imposed by the screen-size of smartphones. However, these were often exacerbated through a combination of social and systemic factors - to the point that their impact is qualitatively and quantitatively different. Simultaneously, however, we find that in some cases Chinese data journalists, at least amongst party media, were protected from pressures such as audience demand, and encouraged to focus on state-of-the-art work. We conclude that what has emerged is a form of ‘data journalism with Chinese characteristics’, and that these characteristics emerge from the interactions between systemic, newsroom and social factors.

Evans, Ryan; Jackson, Daniel; Murphy, Jaron

doi: 10.1080/21670811.2022.2055596pmid: N/A

Abstract Through a mixed methods research design, we address normative aspects of news recommendation engines by examining whether search personalisation and news diversity are evident on Google News in the UK. First, in a quasi-experimental design, we asked a diverse set of participants (N = 78) to search Google News using four search terms and report the first five articles recommended for each term. We found little evidence of news personalisation, which challenges the claim that news search algorithms contribute to weakened viewpoint diversity. We also found a high degree of homogeneity in news search results, with legacy media brands dominating. Second, we conducted a manual content analysis of the articles recommended by Google News for our search terms (N = 192), focusing on favourability towards each term. We found that while there was little relationship between the favourability slant of the articles and political leanings of participants, there were two exceptions: self-identified right-wing participants were more likely to see unfavourable stories about 1) immigration, and 2) a left-wing politician. This reopens the question of news search engines’ contributions to polarisation and viewpoint diversity for certain news consumers.

Schwab, Rafael; Krebs, Isabelle; Bachmann, Philipp

doi: 10.1080/21670811.2022.2076138pmid: N/A

Abstract Due to digitization, traditional media brands are facing hypercompetition. For one thing, media outlets offering journalistic content no longer compete just with each other but also with all sorts of content from various sources, such as corporate publishers. This particularly applies to the information space provided by Google and other search engines. This leads to the question of how traditional media brands prevail in this information space: do traditional media brands have a competitive advantage because users perceive their journalistic content as more valuable in terms of credibility and reputation? Accordingly, this study investigates competition and user selection on Google. Drawing on a representative, experimental selection study of the German-speaking Swiss population (N = 1,100), search engine selection behavior was investigated. Results show that selection preferences do not differ between traditional media brands and other competitors, such as corporate publishers. This poses a major challenge for media brands. However, credibility and reputation significantly influence selection preferences. Thus, media managers should focus on effective branding activities in order to maintain a strong position in the digital information market.

van Drunen, M. Z.; Fechner, D.

doi: 10.1080/21670811.2022.2108868pmid: N/A

Abstract This article explores the relationship between legal and journalistic perspectives on the way editorial independence can be safeguarded in the context of automation. It aims to bridge two discussions. First, the journalism studies literature that has explored how automation challenges the way editors and journalists fulfil their role in newsrooms and society. Second, the legal discussion that is revisiting how the conditions for editorial independence can be created in a media system where automation is increasingly important. To do so, this article contrasts a normative framework that outlines the functions of editorial independence in European media law with interviews with editors and journalists involved in data journalism and news personalisation. It finds excellent potential for a complementary relationship between legal and journalistic perspectives on editorial independence. However, the challenges posed by automation fall outside the mechanisms through which this relationship has traditionally been operationalised.