Data Journalism and the Regeneration of News traces the emergence of data journalism through a scholarly lens. It reveals the growth of data journalism as a subspecialty, cultivated and sustained by an increasing number of professional identities, tools and technologies, educational opportunities and new forms of collaboration and computational thinking. The authors base their analysis on five years of in-depth field research, largely in Canada, an example of a mature media system. The book identifies how data journalism’s development is partly due to it being at the center of multiple crises and shocks to journalism, including digitalization, acute mis- and dis-information concerns and increasingly participatory audiences. It highlights how data journalists, particularly in well-resourced newsrooms, are able to address issues of trust and credibility to advance their professional interests. These journalists are operating as institutional entrepreneurs in a field still responding to the disruption effects of digitalization more than 20 years ago. By exploring the ways in which data journalists are strategically working to modernize the way journalists talk about methods and maintain journalism authority, Data Journalism and the Regeneration of News introduces an important new dimension to the study of digital journalism for researchers, students and educators.

From data-rich infographics to 140 character tweets and activist cell phone photos taken at political protests, 21st century journalism is awash in new ways to report, display, and distribute the news. Computational journalism, in particular, has been the object of recent scholarly and industry attention as large datasets, powerful algorithms, and growing technological capacity at news organizations seemingly empower journalists and editors to report the news in creative ways. Can journalists use data--along with other forms of quantified information such as paper documents of figures, data visualizations, and charts and graphs--in order to produce better journalism? In this book, C.W. Anderson traces the genealogy of data journalism and its material and technological underpinnings, arguing that the use of data in news reporting is inevitably intertwined with national politics, the evolution of computable databases, and the history of professional scientific fields. It is impossible to understand journalistic uses of data, Anderson argues, without understanding the oft-contentious relationship between social science and journalism. It is also impossible to disentangle empirical forms of public truth telling without first understanding the remarkably persistent Progressive belief that the publication of empirically verifiable information will lead to a more just and prosperous world. Anderson considers various types of evidence (documents, interviews, informational graphics, surveys, databases, variables, and algorithms) and the ways these objects have been used through four different eras in American journalism (the Progressive Era, the interpretive journalism movement of the 1930s, the invention of so-called "precision journalism," and today's computational journalistic moment) to pinpoint what counts as empirical knowledge in news reporting. Ultimately the book shows how the changes in these specifically journalistic understandings of evidence can help us think through the current "digital data moment" in ways that go beyond simply journalism.

Data Journalism and the COVID‐19 Disruption offers an international, multidisciplinary account of how and to what extent the COVID‐19 pandemic has been a blessing for data journalism. Bringing together insights into current developments in data journalism during (and since the onset of) the COVID‐19 pandemic from world‐leading data journalism practitioners and academics, this book draws on case studies and examples from different countries to critically reflect on emerging data journalism practices during the pandemic and their sustainability and implications for journalism and newsroom work in the post‐pandemic era. The chapters document changes in the practice and integration of data journalism into newsrooms and the 24/7 news cycle after the unexpected onset of the pandemic and explore how newsrooms and journalists are coping with the sudden and immense demand for data journalism and related challenges. This book also scrutinises the implications for understanding the roles played by newsroom structure and operation, the uncertain nature of data, and the relationship between journalism and other social entities such as audiences and the state in journalism’s development through times of crisis. Offering a timely contribution to the discussions on how data journalism evolved during a time of crisis, this volume will appeal to scholars and students of data journalism, journalism practice, media and communication studies, and media industry studies.

This book is your guide to understanding what journalism is and could be in an age of digital technology and datafication. Journalism today is entwined with the digital. Stories can come from crowdsourcing and content farms. They can incorporate data visualisations and virtual reality. Journalists can find themselves working as self-employed digital entrepreneurs or for tech giants like Google and Facebook. This book explores the development of journalism in this era of digital tech, and big and open data. It explores the crucial new developments of online journalism, data journalism, computational journalism and entrepreneurial journalism, and what this means for our understanding of journalism as a profession, and as a part of society. Using a wealth of international case studies, Jingrong Tong explores contemporary issues such as: AI, Automated news, ‘robot reporters’, and algorithmic accountability. Digital business models, from venture capital to tech start-ups to crowd-funding. Audiences and dissemination in and age of platform capitalism Questions of censorship, democracy and state control. Digital challenges to journalistic autonomy and legitimacy. With clear explanations throughout, Journalism in the Data Age introduces you to a range of ideas, debates and key concepts. It is essential reading for all students of journalism. Dr Jingrong Tong is Senior Lecturer in Digital News Cultures at the University of Sheffield.

How do journalists know what they know? Who gets to decide what good journalism is and when it's done right? What sort of expertise do journalists have, and what role should and do they play in society? Until a couple of decades ago, journalists rarely asked these questions, largely because the answers were generally undisputed. Now, the stakes are rising for journalists as they face real-time critique and audience pushback for their ethics, news reporting, and relevance. Yet the crises facing journalism have been narrowly defined as the result of disruption by new technologies and economic decline. This book argues that the concerns are in fact much more profound. Drawing on their five years of research with journalists in the U.S. and Canada, in a variety of news organizations from startups and freelancers to mainstream media, the authors find a digital reckoning taking place regarding journalism's founding ideals and methods. The book explores journalism's long-standing representational harms, arguing that despite thoughtful explorations of the role of publics in journalism, the profession hasn't adequately addressed matters of gender, race, intersectionality, and settler colonialism. In doing so, the authors rethink the basis for what journalism says it could and should do, suggesting that a turn to strong objectivity and systems journalism provides a path forward. They offer insights from journalists' own experiences and efforts at repair, reform, and transformation to consider how journalism can address its limits and possibilities along with widening media publics.

Considering the interactions between developments in open data and data journalism, Data for Journalism: Between Transparency and Accountability offers an interdisciplinary account of this complex and uncertain relationship in a context of tightening the control over data and weighing transparency against privacy. As data has brought both promise and disruptive changes to societies, the relationship between transparency and accountability has become complicated, and data journalism is practised alongside the contradictory needs of opening up and protecting data. In addition to exploring the benefits of data for journalism, this book addresses the uncertain nature of data and the obstacles preventing data from being fluently accessed and properly used for data reporting. Because of these obstacles, it argues individual data journalists play a decisive role in using data for journalism and facilitating the circulation of data. Frictions in data access, newsrooms’ resources and cultures and data journalists’ skill and data literacy levels determine the degree to which journalism can benefit from data, and these factors potentially exacerbate digital inequalities between newsrooms in different countries and with different resources. As such, the author takes an international perspective, drawing on empirical research and cases from around the world, including countries such as the UK, the US, Germany, Sweden, Australia, India, China and Japan. Introducing a new dimension to the study of developments in journalism and the role of journalism in society, Data for Journalism will be of interest to academics and researchers in the fields of journalism and the sociology of (big and open) data.

This second edition of The Routledge Companion to Digital Journalism Studies offers a truly global and groundbreaking collection of essays addressing the key issues and debates shaping the field of digital journalism studies today. Journalism has arguably faced unprecedented disruption and reconceptualization since the first edition of this Companion was published. Questions over what role journalism and journalists play in society are pervasive, and changes to platforms, products, practices, and audiences are among the forces driving a new research agenda in the field. This newly reorganized second edition addresses developments in technologies, data infrastructures, algorithms, and the businesses behind these technologies, as well as the impact of such developments on the practice of digital journalism. Debates concerning the decline of public trust in journalism, and the blurred distinctions between journalism and other forms of media and communication are also considered. The chapters outline the need for digital competence and literacy within journalism and introduce new methodological approaches, including experimental and arts-based methods, computational methods, and collaborative work. Comprising 54 original essays from distinguished academics across the globe, this book showcases the rich diversity of work that continues to define the field of digital journalism studies and is an essential point of reference for students and researchers alike.