Although data journalism is practiced globally, data journalism research has traditionally focused on a limited set of countries, primarily within the liberal and democratic corporatist media systems. Many recently published studies illustrate a growing scholarly interest in data journalism in other parts of the world, but these studies are still limited in number. This special issue brings together five new empirical studies of data journalism around the world, as well as two commentaries and two book reviews on the topic with the aim of broadening the theoretical, empirical, and geographic perspectives on data journalism. The core of the special issue consists of five national and comparative case studies studying data journalism in Africa, the Arab world, Italy, the UK, and Argentina. Combined, these articles and the other publications in this special issue point to three important contextual factors that shape data journalism worldwide: journalistic cultures, media markets, and the political environment. After a discussion of each of these three factors, areas for future research are proposed.

In the Nordic countries, local and regional newspapers have functioned as keystone media. This article examines the emergence of hyperlocal initiatives as part of evolving local media ecosystems in Finland, analysing the extent and characteristics of hyperlocal media, and how they relate to wider changes in the Finnish media ecosystem. The data gathered on hyperlocal initiatives include a semi-structured survey by phone and online. The research conducted shows that the field is diverse. Rather than considering hyperlocal media in the context of typical publication forms, these newcomers can be best described according to a set of dimensions. Furthermore, the results indicate rather a strong desire to engage people in community building. The emergence of hyperlocal publications means adding a new layer to the Finnish media ecosystem. This development also provides the grounds for further study of the possible emergence of a new media era in Finland.

News automation is an emerging field within journalism, with the potential to transform newswork. Increasing access to data, combined with developing technology, will allow fur-ther inquiries into automated journalism. Producing news text using NLG (natural language generation) is currently largely undertaken in specific, predictable news domains, such assports or finance. This interdisciplinary study investigates how elite media representatives from Finland, Europe and the US imagine the affordances of this emerging technology for their organization. Our analysis shows how the affordances of news automation are imagined as providing efficiency, increasing output and aiding in reallocating resourcesto pursue quality journalism. The affordances are, however, constrained by such factors as access to structured data, the quality of automation and a lack of relevant skills. In its current form, automated text generation is seen as providing only limited benefits to news organizations that are already imagining further possibilities of automation.

This chapter provides an alternative consideration to the conventional view that automation amounts to an existential threat to the work of journalists. It considers the usual discussion about job losses on its head with a claim that “algorithms are a journalist’s new best friend”. The chapter discusses the usual discussion about job losses on its head with a claim that “algorithms are a journalist’s new best friend”. “Robot journalism” is a somewhat banal conceptualization, where illustrators often portray robots writing on computer keyboards instead of visually less attractive software. There has been a revolution in the production of news by smart machines thanks to the advancement of Natural Language Generation technologies, thus extending human capabilities and creating augmented journalism. Automated routine news is gradually complementing manually produced journalistic texts, creating emotional stress in many newsrooms. News alarms like those based on automated searches of police arrest records that Los Angeles Times crime reporters are using will be much more common.