Algorithmic

What makes information feel true or compelling in our contemporary digital societies? This book brings together different disciplinary understandings of “authenticity” in order to find alternative ways to approach mis- and disinformation that go beyond contemporary fact-checking and its search for the “authentic” truth.

Algorithmic Authenticity

An Overview

What makes information feel true or compelling in our contemporary digital societies? This book brings together different disciplinary understandings of “authenticity” in order to find alternative ways to approach mis- and disinformation that go beyond contemporary fact-checking and its search for the “authentic” truth. Patterned under the algorithmic flows of digital capitalism, authenticity itself is subject to variation, iteration, and outside influence. Linking cross-disciplinary research on the history and practices of algorithmic authenticity points to new research questions to understand the impact of algorithmic authenticity on social life and its role in contemporary information disorder.

 

Contributors: Anthony Glyn Burton, Wendy Hui Kyong Chun and Liliana Bounegru, Melody Devries, Amy Harris, hannah holtzclaw, Ioana Jucan, Alex Juhasz, D. W. Kamish, Ganaele Langlois, Jasmine Proctor, Christine Tomlinson, Roopa Vasudevan, Esther Weltevrede

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Publishing Year
2023
Language
English
Pages
138
Print Edition Price
€ 14.90 RRP
Downloads
Cover
License
CC BY-SA 4.0
ISBNs
978-3-95796-210-2 (Print)
978-3-95796-211-9 (PDF)
DOI
10.14619/2102
Available as
Print, PDF

The Authors

Anthony Glyn Burton is a Mellon-SFU Data Fluencies Fellow at the Digital Democracies Institute and a PhD Candidate in the School of Communication at Simon Fraser University.

Anthony Glyn Burton's Author Profile

Wendy Hui Kyong Chun is Simon Fraser University’s Canada 150 Research Chair in New Media in SFU School of Communication. She is the author of several books, including most recently Updating to Remain the Same: Habitual New Media.

Wendy Hui Kyong Chun's Author Profile