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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.
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.
Acknowledgements
Chapter One: Introduction
Chapter Two: The Idea of Data, Documents, and Evidence in Early
20th Century Journalism
Chapter Three: Journalism Interprets, Sociology Scientizes:
Boundary Work Between Empirical Occupations in the 1920s and
Beyond
Chapter Four: Context, Social Science, and the Birth of Precision
Journalism
Chapter Five: Precision Becomes Data
Chapter Six: Databases, Stories, Databases: Narrative, Semantics,
and Computational Journalism
Chapter Seven: Three Overview Cases: Varieties of Information in
the Digital Age
Chapter Eight: Solidarity and Uncertainty
Appendix: On Objects, Objectivity, and Method
Primary Sources and Archives
Bibliography
Index
C.W. Anderson is Professor of Media and Communication at the University of Leeds. He studies journalism, politics, and how the production of public knowledge is being transformed in the digital age. He is the author, co-author, or co-editor of several books including Rebuilding the News, Remaking News (with Pablo Boczkowski), and News: What Everyone Needs to Know (with Michael Schudson and Len Downie).
"...C. W. Anderson's book-length study significantly broadens our perspective on data journalism and the technological, institutional, practical, and intellectual settings that allowed it to emerge and thrive." -- Christian Pentzold, University of Bremen, The International Journal of Press/Politics
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