For journalists, numerous digital tools such as spreadsheets or web application are readily available for easy implementation. However, using programming to build or modify scripts has been an unexplored option for many journalists. Programming requires skills from the ICT professions, so when journalists find coding to be an efficient tool, do they stick with their old methods and ask ICT specialists for help, or do they learn to code themselves? This article is a qualitative study of the methodological reports pertaining to investigative projects nominated for the Norwegian journalism award SKUP. In these reports, programming has been used as a tool in 109 projects. The study examines which problems are solved using coding and the arguments for choosing this tool over simpler methods. It also looks at who performs the coding and how the editorial teams collaborate to reap the benefits of coding. The findings show that many journalists often find it difficult to collaborate with ICT specialists. They would therefore rather learn basic coding skills themselves. They follow a “do-it-yourself” philosophy and learn simple and open programming languages such as SQL, Python just well enough to achieve their goals.

Sharing and discussing visual images in WhatsApp groups functions as a form of phatic news sharing to achieve a sense of togetherness and sociability. We explore how visual media content shared in personal WhatsApp interactions during the first strict lockdown months of the COVID-19 pandemic functions as phatic news. Our study addresses a gap in journalism studies in researching news-related and visual content from user perspectives. Our article provides insights into how the “semi-private” space of WhatsApp offers people a digital communication space to deal with becoming a news subject during the crisis: people appropriate news by shaping it into different visual forms which can be attractively shared on WhatsApp. We focus on working adults (aged 25–49) in urban areas in Spain, Italy, and the Netherlands. Visual phatic news sharing on WhatsApp combines public and private aspects, especially how people address issues of public concern through their private WhatsApp communication. Our conclusions reveal how WhatsApp functions as a sense-making practice and vehicle for ontological security in dealing with the fearful and unsettling crisis situation. The visual images shared are a hybrid form of communication, blurring boundaries between private life and public concerns presented on the news.

Data has become an increasingly important commodity for news organizations. The capability to extract, store, and analyze data is also central to organizational decision-making. Drawing on the concept of epistemic infrastructures, this study sheds light on organizational datafication in journalism. Analyzing job advertisements of incumbent broadcast, print legacy, and online-only news outlets in the US and UK, this study traces material underpinnings of data architectures, networks of data agents, and epistemic data paradigms in news organizations. We show that a professional data elite of data analysts, engineers, and product developers serves as an epistemic community that consolidates power through epistemic authority and reinforces epistemic paradigms in journalism. We describe epistemic data infrastructures in the journalistic field and highlight how reliance on these infrastructures contributes to ethical challenges that news organizations are ill-equipped to address. We conclude that news organizations are deeply engaged in fostering epistemic infrastructures and that by acknowledging them, we can better analyze socio-technological changes in journalism and its consequences.

The emerging use of Conversational Agents (CAs), such as Google Assistant, highlights the role of algorithmic gatekeeping power in news consumption. However, our knowledge of the effects of CAs on shaping the public’s perception of the most important topics (issue salience) is limited. To investigate this, we conducted a seven-day longitudinal survey in the Netherlands, comparing the most important issues reported by users (N = 352) across various channels, including CAs, social media, and news websites. Our aim was to analyze how CAs influence the transfer of issue salience from the channel to the user. While our hypotheses were not supported, different patterns emerged. Users consuming news through CAs exhibited a have a lower probability of agreeing on the most important issues in the Netherlands compared to participants consuming information on social media and news websites. This suggests that news consumption through CAs may offer less shared context compared to other channels. Furthermore, trust in the channel and attention to the news were found to be significant predictors of agreement on issue salience. These findings raise important questions for further research, particularly regarding the impact and democratic role of CAs within the broader news ecosystem.

The question of “who is a journalist?” has animated much discussion in journalism scholarship. Such discussions generally stem from the intersecting technological, economic, and social transformations journalism has faced in the twenty-first century. An equally relevant aspect, albeit one that has hitherto been less studied, is what a journalist looks like. Some studies have tackled this through, for example, examining depictions of journalists in popular culture, but artificial intelligence understandings of what a journalist is and what they look like have yet to receive research attention. While AI-enabled generative art has existed since the late 1990s, the ease and accessibility of these processes has greatly been boosted by providers like Midjourney which emerged since the 2020s and allow those without programming skills to easily create algorithmic images from text prompts. This study analyzes 84 images generated by AI from four “generic” keywords (“journalist,” “reporter,” “correspondent,” and “the press”) and three “specialized” ones (“news analyst,” “news commentator,” and “fact-checker”) over a six-month period. The results reveal an uneven distribution of gender and digital technology between the generic and specialized roles and prompt reflection on how AI perpetuates extant biases in the social world.

Click to increase image sizeClick to decrease image size Disclosure StatementNo potential conflict of interest was reported by the author(s).

In order to better understand alternative news media, we need to focus more centrally on the audiences that regularly consume them. This special issue, entitled “Contesting the Mainstream: Understanding Alternative News Media,” advances such an audience turn. In the introduction, we outline how scholars have understood and characterized alternative news audiences. These have ranged from seeing them as (i) ideal participants and activists; as (ii) being misinformed and manipulated; and as (iii) being critical users. Drawing on studies published in this special issue, we highlight how these studies provide new and revealing empirical insights that advance all three perspectives. Taken together, the articles make a strong argument to move beyond binary ideations of normatively “good” or “bad” alternative news audiences. In our view, they signal the need to better understand the complexity behind audience engagement not just with alternative news media but mainstream journalism more generally. Based on this argument, we identify several starting points for moving the field forward with such an audience turn in mind.

Scholarship has now recognized the potentially detrimental effects of social media on political knowledge. At the same time, a separate but similar line of work has raised concerns that these platforms are the primary vector of political misinformation. Despite the renewed focus on misinformation studies, the question as to whether political knowledge and susceptibility to misinformation are related remains open. If they are indeed related, we still know little about the underlying cognitive mechanisms that drive political learning when people rely on social media for news. Based on a two-wave panel survey collected during the 2020 U.S. presidential election, we found that social media news use fosters the news-finds-me perception (particularly among those who feel overwhelmed with the volume of information available on social media). This, in turn, leads people to be both uninformed and misinformed about politics and current affairs. Implications for democracy are discussed.

“Mainstream media” and “mainstream journalism” have become significant concepts in political, popular, and academic discourse in recent years. They are key in how media, communication, and journalism scholars have been, and continue to be, concerned with relational dimensions in their work. However, the meaning of the word “mainstream” is often taken for granted. How and by whom this concept is used among media, communication, and journalism scholars is therefore of great importance. This article analyses uses of “mainstream” in academic discourse to unpack the various meanings ascribed to it. Through computational Topic Modelling Analysis and qualitative context analysis we analyse the relations, positions, normative underpinnings, and appropriate uses of “mainstream” in 779 journal articles published between 2000 and 2022. The analysis is framed by Wittgenstein’s notion of “language-game” as a way of analysing the meaning-making process constituted by uses of “mainstream” in these articles. We argue that “mainstream” resembles a “boundary object” but conclude that the rules of the “mainstream language-game” are confusing and need revisions, and that the concept only functions as an illusory boundary object, which is arguably problematic.

As political alternative media have become increasingly prominent, a key question is whether they are likely to strengthen or weaken how established democracies work. The purpose of this commentary is hence to discuss this question, focusing specifically on whether political alternative media are likely or not to contribute to a more informed citizenry. Although there may be great differences between political alternative media, the overall conclusion is that political alternative media from a democratic perspective represent a problem rather than a solution to democracy’s problem, and that this is due both to the content in them and the motivations people have for using them.