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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.
Faced with a full-blown crisis, a growing number of journalists are engaging in seemingly unjournalistic practices such as creating and maintaining databases, handling algorithms, or designing online applications. “Data journalists” claim that these approaches help the profession demonstrate greater objectivity and fulfill its democratic mission. In their view, computational methods enable journalists to better inform their readers, more closely monitor those in power, and offer deeper analysis. In Computing the News, Sylvain Parasie examines how data journalists and news organizations have navigated the tensions between traditional journalistic values and new technologies. He traces the history of journalistic hopes for computing technology and contextualizes the surge of data journalism in the twenty-first century. By importing computational techniques and ways of knowing new to journalism, news organizations have come to depend on a broader array of human and nonhuman actors. Parasie draws on extensive fieldwork in the United States and France, including interviews with journalists and data scientists as well as a behind-the-scenes look at several acclaimed projects in both countries. Ultimately, he argues, fulfilling the promise of data journalism requires the renewal of journalistic standards and ethics. Offering an in-depth analysis of how computing has become part of the daily practices of journalists, this book proposes ways for journalism to evolve in order to serve democratic societies.
When you combine the sheer scale and range of digital information now available with a journalist’s "nose for news" and her ability to tell a compelling story, a new world of possibility opens up. With The Data Journalism Handbook, you’ll explore the potential, limits, and applied uses of this new and fascinating field. This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both. Examine the use of data journalism at the BBC, the Chicago Tribune, the Guardian, and other news organizations Explore in-depth case studies on elections, riots, school performance, and corruption Learn how to find data from the Web, through freedom of information laws, and by "crowd sourcing" Extract information from raw data with tips for working with numbers and statistics and using data visualization Deliver data through infographics, news apps, open data platforms, and download links
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.
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.
Between the 1970s and the 1990s American journalists began telling the news by telling stories. They borrowed narrative techniques, transforming sources into characters, events into plots, and their own work from stenography to anthropology. This was more than a change in style. It was a change in substance, a paradigmatic shift in terms of what constituted news and how it was being told. It was a turn toward narrative journalism and a new culture of news, propelled by the storytelling movement. Thomas Schmidt analyzes the expansion of narrative journalism and the corresponding institutional changes in the American newspaper industry in the last quarter of the twentieth century. In doing so, he offers the first institutionally situated history of narrative journalism’s evolution from the New Journalism of the 1960s to long-form literary journalism in the 1990s. Based on the analysis of primary sources, industry publications, and oral history interviews, this study traces how narrative techniques developed and spread through newsrooms, advanced by institutional initiatives and a growing network of practitioners, proponents, and writing coaches who mainstreamed the use of storytelling. Challenging the popular belief that it was only a few talented New York reporters (Tome Wolfe, Jimmy Breslin, Gay Talese, Joan Didion, and others) who revolutionized journalism by deciding to employ storytelling techniques in their writing, Schmidt shows that the evolution of narrative in late twentieth century American Journalism was more nuanced, more purposeful, and more institutionally based than the New Journalism myth suggests.
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.
Recent advances in digital technologies are allowing data journalists to find and tell stories in new and visually exciting ways, often working in collaboration with developers, statisticians and designers. It's a new frontier for many newsrooms, but not without its own teething pains. This much anticipated follow-up volume to the bestselling Data Journalism: Mapping the future features 30 chapters from journalists, developers and academics on both sides of the Atlantic and further afield. It is an essential primer for wannabe data hacks and others interested in the trade. The Editors: Tom Felle lectures at the Department of Journalism, City University London; John Mair is a journalism academic and former BBC director/producer; Damian Radcliffe is Carolyn S Chambers Professor in Journalism at the University of Oregon. Contributors include Simon Rogers, Data Editor at Google; Nick Phipps, an editor at Sky News; Helena Bengtsson, Editor, Data Projects at the Guardian; Megan Lucero, Data Journalism Editor at The Times and The Sunday Times, London; and Steve Doig, Knight Chair in Journalism at the Walter Cronkite School of Journalism and Mass Communication, Arizona State University. Kathryn Corrick, independent consultant; Eva Constantaras, Internews; Andy Dickinson, University of Central Lancashire; Gavin Freeguard, Institute for Government; Adam Frost and Tobias Sturt, Graphic; Jan Goodey, Kingston University, London; Alexander B Howard, writer and editor, Washington, DC; Kathryn Hayes, University of Limerick, Ireland; Jonathan Hewett, City University London; Bella Hurrell and John Walton, BBC Visual Journalism team; Liz Hannaford, Manchester Metropolitan University; Gabriel Keeble-Gagnere, Murdoch University, Perth, Australia; Isabelle Marchand, data journalist, PRISM; Martin Moore and Gordon Neil Ramsay, Kings College London; Matteo Moretti, Free University of Bozen-Bolzano; Sanjit Oberai, Quintillion; AEndrew Rininsland, The Times and The Sunday Times, London; Zara Rahman, researcher and writer, Berlin, Germany; Emily Shackleton, digital journalist, London; Jonathan Spencer, BBC News; Nicole Smith Dahmen, University of Oregon; Jonathan Stoneman, former journalist at the BBC Word Service; and Jacqui Taylor, founder, FlyingBinary."
From the quality of the air we breathe to the national leaders we choose, data and statistics are a pervasive feature of daily life and daily news. But how do news, numbers and public opinion interact with each other – and with what impacts on society at large? Featuring an international roster of established and emerging scholars, this book is the first comprehensive collection of research into the little understood processes underpinning the uses/misuses of statistical information in journalism and their socio-psychological and political effects. Moving beyond the hype around “data journalism," News, Numbers and Public Opinion delves into a range of more latent, fundamental questions such as: · Is it true that most citizens and journalists do not have the necessary skills and resources to critically process and assess numbers? · How do/should journalists make sense of the increasingly data-driven world? · What strategies, formats and frames do journalists use to gather and represent different types of statistical data in their stories? · What are the socio-psychological and political effects of such data gathering and representation routines, formats and frames on the way people acquire knowledge and form attitudes? · What skills and resources do journalists and publics need to deal effectively with the influx of numbers into in daily work and life – and how can newsrooms and journalism schools meet that need? The book is a must-read for not only journalists, journalism and media scholars, statisticians and data scientists but also anybody interested in the interplay between journalism, statistics and society.