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Framing big dataa linguistic and dis...
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Paganoni, Maria Cristina.
Framing big dataa linguistic and discursive approach /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Framing big databy Maria Cristina Paganoni.
Reminder of title:
a linguistic and discursive approach /
Author:
Paganoni, Maria Cristina.
Published:
Cham :Springer International Publishing :2019.
Description:
xi, 116 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Big data.
Online resource:
https://doi.org/10.1007/978-3-030-16788-2
ISBN:
9783030167882$q(electronic bk.)
Framing big dataa linguistic and discursive approach /
Paganoni, Maria Cristina.
Framing big data
a linguistic and discursive approach /[electronic resource] :by Maria Cristina Paganoni. - Cham :Springer International Publishing :2019. - xi, 116 p. :ill., digital ;24 cm.
Chapter 1: Framing the Debate on Big Data -- Chapter 2: Big Data in the News Media -- Chapter 3: Big Data and Healthcare -- Chapter 4: Legal and Ethical Implications in the Big Data Debate -- Chapter 5: Concluding Remarks.
This book addresses big data as a socio-technical construct with huge potential for innovation in key sectors such as healthcare, government and business. Big data and its increasingly widespread use in such influential spheres can generate ethically controversial decisions, including questions surrounding privacy, consent and accountability. This book attempts to unpack the epistemological implications of the term 'big data', as well as the opportunities and responsibilities which come with it. The author analyses the linguistic texture of the big data narrative in the news media, in healthcare and in EU law on data protection, in order to contribute to its understanding from the critical perspective of language studies. The result is a study which will be of interest to students and scholars working in the digital humanities, corpus linguistics, and discourse studies. Maria Cristina Paganoni is an Associate Professor of English Language and Translation at the University of Milan, Italy. Her research interests include new media, place and city branding, heritage and tourism, investigated with the tools of linguistics, Discourse Analysis and social semiotics. She is the author of City Branding and New Media (Palgrave, 2015)
ISBN: 9783030167882$q(electronic bk.)
Standard No.: 10.1007/978-3-030-16788-2doiSubjects--Topical Terms:
609582
Big data.
LC Class. No.: QA76.9.B45 / P343 2019
Dewey Class. No.: 005.7
Framing big dataa linguistic and discursive approach /
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Chapter 1: Framing the Debate on Big Data -- Chapter 2: Big Data in the News Media -- Chapter 3: Big Data and Healthcare -- Chapter 4: Legal and Ethical Implications in the Big Data Debate -- Chapter 5: Concluding Remarks.
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This book addresses big data as a socio-technical construct with huge potential for innovation in key sectors such as healthcare, government and business. Big data and its increasingly widespread use in such influential spheres can generate ethically controversial decisions, including questions surrounding privacy, consent and accountability. This book attempts to unpack the epistemological implications of the term 'big data', as well as the opportunities and responsibilities which come with it. The author analyses the linguistic texture of the big data narrative in the news media, in healthcare and in EU law on data protection, in order to contribute to its understanding from the critical perspective of language studies. The result is a study which will be of interest to students and scholars working in the digital humanities, corpus linguistics, and discourse studies. Maria Cristina Paganoni is an Associate Professor of English Language and Translation at the University of Milan, Italy. Her research interests include new media, place and city branding, heritage and tourism, investigated with the tools of linguistics, Discourse Analysis and social semiotics. She is the author of City Branding and New Media (Palgrave, 2015)
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000000175429
電子館藏
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EB QA76.9.B45 P131 2019 2019
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https://doi.org/10.1007/978-3-030-16788-2
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