Newsrooms are a social context in which numerous relationships exist and influence news work—be it with other journalists, the audience, and technology. As some of these relations change due to technological innovations, new hybrid contexts—technologies that are interwoven with newsroom values, routines, and socio-cultural experiences—can emerge. One key question is how journalists conceptualise and interact with such technologies, and to what degree they retain (creative) agency in the process. Therefore, this study evaluates the intersection of automated journalism and journalistic role conceptions. Using Hanitzsch’s and Vos’s circular model of journalistic roles (2017) and Deuze’s understanding of journalism as an ideology (2005) as a theoretical framework, this study examines some of the discursive aspects of automated journalism by asking: To what extent are journalistic roles (a) challenged or (b) advanced as a result of automated journalism? Our findings more closely align with the latter, pointing to a strong sense of discursive maintenance of journalists’ roles and their core skillset and thus suggesting a high degree of ideological continuity in the face of industrial disruption. It concludes with an agenda for future research and stresses that at times when journalism and automation intersect, the field would benefit from incorporating emerging conceptual frameworks such as human–machine communication.

As a consequence of digitization and other environmental trends, journalism is changing its forms and arguably also its functions—both in fundamental ways. While ‘legacy’ news media continue to be easily distinguishable by set characteristics, new content providers operating in an increasingly dense, chaotic, interactive, and participatory information environment still remain somewhat understudied. However, at a time when non-traditional formats account for an ever-growing portion of journalistic or para-journalistic work, there is an urgent need to better understand these new peripheral actors and the ways they may be transforming the journalistic field. While journalism scholarship has begun to examine peripheral actors’ motivations and conceptualizations of their roles, our understanding is still fairly limited. This relates particularly to comparative studies of peripheral actors, of which there have been very few, despite peripheral journalism being a global phenomenon. This study aims to address this gap by presenting evidence from 18 in-depth interviews with journalists in Australia, Germany, and the UK. In particular, it examines how novel journalistic actors working for a range of organisations discursively contrast their work from that of others. The findings indicate that journalists’ motivations to engage in journalism in spite of the rise of precarious labour were profoundly altruistic: Indeed, journalists pledged allegiance to an ideology of journalism still rooted in a pre-crisis era—one which sees journalism as serving a public good by providing an interpretative, sense-making role.

The use of social media as a source of news is entering a new phase as computer algorithms are developed and deployed to detect, rank, and verify news. The efficacy and ethics of such technology is the subject of this article, which examines the SocialSensor application, a tool developed by a multidisciplinary European Union research project. The results suggest that computer software can be used successfully to identify trending news stories, allow journalists to search within a social media corpus, and help verify social media contributors and content. However, such software also raises questions about accountability as social media is algorithmically filtered for use by journalists and others. Our analysis of the inputs SocialSensor relies on shows biases towards those who are vocal and have an audience, many of whom are men in the media. We also reveal some of the technology’s temporal and topic preferences. The conclusion discusses whether such biases are necessary for systems like SocialSensor to be effective. The article also suggests that academic research has failed to recognise fully the changes to journalists’ sourcing practices brought about by social media, particularly Twitter, and provides some countervailing evidence and an explanation for this failure.

The rapid acceleration of artificial intelligence (AI) and, more recently, generative AI is reshaping journalism in ways that extend far beyond earlier forms of news automation. As generative AI tools become widely accessible and capable of processing unstructured data, longstanding definitions of automated journalism—once centered on structured datasets and template-based text generation—are being fundamentally reconfigured. This paper presents the most comprehensive and up-to-date systematized review of automated journalism scholarship, expanding on earlier research by synthesizing 185 peer-reviewed, English studies published between 2012 and 2024 about machine-generated textual news content published online. Through a rigorously designed search strategy across four major social science databases, this review maps how the field’s conceptual, methodological, and geographical contours have transformed as AI and generative AI become increasingly ubiquitous. The findings show a surge of research in 2024 alone, as well as the emergence of more than 150 overlapping terms used to describe AI- and algorithmically generated news, illustrating significant conceptual fragmentation. Despite no overly dominant theories, concepts or frameworks, key themes include credibility and trust, human–machine collaboration, newsroom adoption and institutional logics, transparency and disclosure, and the ethical and regulatory challenges introduced by increasingly sophisticated AI systems. By consolidating patterns, evaluating an expanded selection of key terms, and assessing theoretical and conceptual frameworks, this review demonstrates how AI and especially generative AI reflect the speed of industrial change, but also the lack of shared academic frameworks to make sense of that change.

Using the Egyptian Revolution as a case study, this article studies journalistic sourcing and verification through in-depth interviews with journalists in the United Kingdom. While the coverage of the event in the British media was dominated by civic, unofficial sources, interviews conducted in 2014 revealed that journalists only included these if no other sources were available. In fact, journalists voiced concern with regards to verification of online sources, and rarely included these as direct, first-hand accounts. Follow-up interviews conducted in 2020 point to developments journalism practice has undergone since, particularly in relation to open-source content verification. Overall, the picture we paint of British journalists’ handling of content sourced from social media is one wedged between expressed enthusiasm and cautious scepticism.