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Against the hypothesis of the end of privacy: An agent-based modeling approach to social media

Against the hypothesis of the end of privacy: An agent-based modeling approach to social media

Tubaro, Paola, Casilli, Antonio A. and Sarabi, Yasaman (2014) Against the hypothesis of the end of privacy: An agent-based modeling approach to social media. SpringerBriefs in Digital Spaces . Springer International Publishing, Cham / Heidelberg / New York / Dordrecht / London. ISBN 978-3-319-02455-4

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Abstract

Several prominent public voices have advanced the hypothesis that networked communications erode the value of privacy in favor of a transparent connected existence. Especially younger generations are often described as prone to live "open digital lives". This hypothesis has raised considerable controversy, polarizing the reaction of its critics as well as of its partisans. But how likely is the "end of privacy"? Under which conditions might this scenario come to be? What are the business and policy implications? How to ethically assess risks and opportunities? To shed light on the co-evolution and mutual dependencies of networked structures and individual and collective strategies towards privacy, this book innovatively uses cutting-edge methods in computational social sciences to study the formation and maintenance of online social networks. The findings confound common arguments and clearly indicate that Internet and social media do not necessarily entail the end of privacy. Publicity is not "the new norm": quite to the contrary, the book makes the case that privacy is a resilient social force, resulting from a set of interconnected behaviors of Internet users.

Item Type: Book
Uncontrolled Keywords: social media, privacy, agent-based computer simulation, social capital
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / Department / Research Group: Faculty of Business > Centre for Business Network Analysis
Faculty of Business > Department of International Business & Economics
Related URLs:
Last Modified: 18 Oct 2016 08:55
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/10324

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