Framing Big Data A Linguistic and Discursive Approach /

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 surr...

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Κύριος συγγραφέας: Paganoni, Maria Cristina (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Palgrave Pivot, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη: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).
Φυσική περιγραφή:XI, 116 p. 1 illus. online resource.
ISBN:9783030167882
DOI:10.1007/978-3-030-16788-2