Big data is marked by staggering growth in the collection and analysis of digital trace information regarding human and natural activity, bound up in and enabled by the rise of persistent connectivity, networked communication, smart machines, and the internet of things. In addition to their impact on technology and society, these developments have particular significance for the media industry and for journalism as a practice and a profession. These data-centric phenomena are, by some accounts, poised to greatly influence, if not transform, some of the most fundamental aspects of news and its…mehr
Big data is marked by staggering growth in the collection and analysis of digital trace information regarding human and natural activity, bound up in and enabled by the rise of persistent connectivity, networked communication, smart machines, and the internet of things. In addition to their impact on technology and society, these developments have particular significance for the media industry and for journalism as a practice and a profession. These data-centric phenomena are, by some accounts, poised to greatly influence, if not transform, some of the most fundamental aspects of news and its production and distribution by humans and machines. What such changes actually mean for news, democracy, and public life, however, is far from certain. As such, there is a need for scholarly scrutiny and critique of this trend, and this volume thus explores a range of phenomena-from the use of algorithms in the newsroom, to the emergence of automated news stories-at the intersection between journalism and the social, computer, and information sciences. What are the implications of such developments for journalism's professional norms, routines, and ethics? For its organizations, institutions, and economics? For its authority and expertise? And for the epistemology that underwrites journalism's role as knowledge-producer and sense-maker in society? 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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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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