What does big data mean for journalism? From the use of algorithms in the newsroom to the rise of automated news stories, this book explores cases, concepts, and critiques for making sense of data-centric practices and philosophies, and their implications for journalism-its norms and values, economics and ethics, and professional authority in the digital era. Altogether, this book offers a first step in understanding what big data means for journalism. This book was originally published as a special issue of Digital Journalism.
What does big data mean for journalism? From the use of algorithms in the newsroom to the rise of automated news stories, this book explores cases, concepts, and critiques for making sense of data-centric practices and philosophies, and their implications for journalism-its norms and values, economics and ethics, and professional authority in the digital era. Altogether, this book offers a first step in understanding what big data means for journalism. This book was originally published as a special issue of Digital Journalism.
Seth C. Lewis is the inaugural Shirley Papé Chair in Electronic and Emerging Media in the School of Journalism and Communication at the University of Oregon, Eugene, OR, USA. He is also a visiting fellow with the Information Society Project at Yale Law School, CT, USA. His widely published research explores the digital transformation of journalism, with a focus on the human-technology interactions and media innovation processes associated with data, code, analytics, social media, and related phenomena. He is co-editor of Boundaries of Journalism: Professionalism, Practices, and Participation (Routledge, 2015), and is on the editorial boards of New Media & Society, Social Media + Society, Digital Journalism, and Journalism & Mass Communication Quarterly, among other journals.
Inhaltsangabe
Introduction - Journalism in an Era of Big Data: Cases, concepts, and critiques 1. Clarifying Journalism's Quantitative Turn: A typology for evaluating data journalism, computational journalism, and computer-assisted reporting 2. Between the Unique and the Pattern: Historical tensions in our understanding of quantitative journalism 3. Data-driven Revelation? Epistemological tensions in investigative journalism in the age of "big data" 4. From Mr. and Mrs. Outlier to Central Tendencies: Computational journalism and crime reporting at the Los Angeles Times 5. Algorithmic Accountability: Journalistic investigation of computational power structures 6. The Robotic Reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority 7. Waiting for Data Journalism: A qualitative assessment of the anecdotal take-up of data journalism in French-speaking Belgium 8. Big Data and Journalism: Epistemology, expertise, economics, and ethics
Introduction - Journalism in an Era of Big Data: Cases, concepts, and critiques 1. Clarifying Journalism's Quantitative Turn: A typology for evaluating data journalism, computational journalism, and computer-assisted reporting 2. Between the Unique and the Pattern: Historical tensions in our understanding of quantitative journalism 3. Data-driven Revelation? Epistemological tensions in investigative journalism in the age of "big data" 4. From Mr. and Mrs. Outlier to Central Tendencies: Computational journalism and crime reporting at the Los Angeles Times 5. Algorithmic Accountability: Journalistic investigation of computational power structures 6. The Robotic Reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority 7. Waiting for Data Journalism: A qualitative assessment of the anecdotal take-up of data journalism in French-speaking Belgium 8. Big Data and Journalism: Epistemology, expertise, economics, and ethics
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