The availability of data feeds, the demand for news on digital devices, and advances in algorithms are helping to make automated journalism more prevalent. This article extends the literature on the subject by analysing professional journalists' experiences with, and attitudes to, the technology. Uniquely, the participants were drawn from a range of news organizations-including the BBC, CNN, and Thomson Reuters-and had first-hand experience working with robo-writing software provided by one of the leading technology suppliers. The results reveal journalists' judgements on the limitations of automation, including the nature of its sources and the sensitivity of its "nose for news". Nonetheless, journalists believe that automated journalism will become more common, increasing the depth, breadth, specificity, and immediacy of information available. While some news organizations and consumers may benefit, such changes raise ethical and societal issues and, counter-intuitively perhaps, may increase the need for skills-news judgement, curiosity, and scepticism-that human journalists embody.

This special issue examines the growing importance of algorithms and automation in the gathering, composition, and distribution of news. It connects a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these articles share some of the noble ambitions of the pioneering publications on 'reporting algorithms', such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems, to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematize computational journalism by, for example, pointing out some of the challenges inherent in applying AI to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner.

This study examines how female football (soccer) fans use the social media platform Tumblr to interact and talk about their fandom, what purposes Tumblr serves for them, and why they prefer it to other social media platforms. As women are often marginalised in offline and online sports discourse, Tumblr’s football fandom was chosen to investigate how women experience their fandom on a platform with a mostly female and young user population. The results of 14 in-depth qualitative interviews with heavily invested female Tumblr users show that the fandom’s communication culture allows fans to interact in a variety of creative ways that involve the use of a specialist vocabulary. This Tumblr fandom is overwhelmingly female, which makes the interviewees feel that they can talk freely about football. Thus, Tumblr has the potential to serve as a safe space for female fans. Yet, its highly opinionated discussions and rivalries mirror those in the traditional football fandom. This study contributes to the literature that explores how women express their sports fandom online and demonstrates how they have found a niche in which to discuss their favourite sport on their own terms.

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Journalism professionals and media experts have traditionally used normatively formed criteria to evaluate news quality. Although the digital news media environment has enabled journalists to respond at unprecedented speed to audience consumption patterns, little academic research has systematically addressed how audiences themselves perceive and evaluate news, and even less has focused on audio-visual news. To help fill this research gap, we conducted in-depth group interviews with 22 online news video consumers in the UK to explore their perceptions of online news videos-an increasingly popular news format. Thematic analyses suggest audiences evaluate online news videos using a complex and interwoven set of criteria, which we group under four headings: antecedents of perceptions, emotional impacts, news and editorial values and production characteristics. Some of these criteria can be positioned clearly in relation to the literature on news quality in general, while our documentation of the others contributes new, format-specific knowledge. Our findings offer journalists practical insights into how audiences perceive and evaluate a host of characteristics of online news videos, while our conceptual framework provides a foundation for further academic research on audience evaluations of online news videos, and even audio-visual news more generally.

This study examines how algorithmic processing affects structures and practices in sports journalism in Germany. A multi-level perspective is used to determine which strategies data providers, software providers, and media outlets use to develop automated reporting, which compiles perspectives across the entire line of news production. The results of 11 in-depth interviews show that non-journalistic actors are vital partners in the news production process, as all actors work together in data handling, training, and software development. Moreover, automation can generate additional content such as match and historical coverage to help address shortfalls in capacity. However, given the business case for automation, amateur football (soccer) is currently the only viable candidate for its use. Many actors involved in the process argue that automated content is an added value for their readers, but claim that content quality has to be put before quantity. This means that some media outlets edit automated articles to increase the quality of their sports journalism, but that this is done only on a small scale. Media outlets do not perceive their roles to be changing, but see automation as a helpful tool that complements their work; a few use automatically created articles as a baseline for in-depth reporting. Moreover, the so-called ‘meta-writer’ has not become a reality yet, as data-processing and news writing are still kept separate. This article sheds new light on the use of automation in the sports beat, highlighting the growing role of non-journalistic actors in the news production process.

This special issue examines the growing importance of algorithms and automation in the gathering, composition, and distribution of news. It connects a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these articles share some of the noble ambitions of the pioneering publications on 'reporting algorithms', such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems, to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and reusing content. Thirdly, they problematize computational journalism by, for example, pointing out some of the challenges inherent in applying AI to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner.

During the COVID-19 pandemic, TV broadcasters and clubs were challenged to provide alternative formats and content for fans of Germany’s favorite sport, football [soccer]. Thus, they emulated matchdays and created a Bundesliga feeling in new ways. The authors focus on this alternative creative sports coverage during the Coronavirus crisis and consider the effect on the audience. TV broadcasters, for instance, recreated Bundesliga matchdays through broadcasting historical matches, sticking with the original fixtures from before the crisis, while offering renewed commentary. Clubs conducted the Bundesliga Home Challenge, that is, FIFA20 videogame matches with their professional and eSport players, covering these matches on Twitter and their website. The authors argue that these efforts of keeping up the beloved structure of daily sports events satisfy social and entertaining belongings that are normally continually recreated through watching and talking about live sports events. Moreover, they discuss the possible sustainability of these innovative ways of sport communication.