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Algorithmic Gatekeeping for Professional Communicators

Authors :
van Dalen, Arjen
Publication Year :
2023
Publisher :
Taylor & Francis; Routledge, 2023.

Abstract

This book provides a critical study of the power, trust, and legitimacy of algorithmic gatekeepers. The news and public information which citizens see and hear is no longer solely determined by journalists, but increasingly by algorithms. Van Dalen demonstrates the gatekeeping power of social media algorithms by showing how they affect exposure to diverse information and misinformation and shape the behaviour of professional communicators. Trust and legitimacy are foregrounded as two crucial antecedents for the acceptance of this algorithmic power. This study reveals low trust among the general population in algorithms performing journalistic tasks and a perceived lack of legitimacy of algorithmic power among professional communicators. Drawing on case studies from YouTube and Instagram, this book challenges technological deterministic discourse around ""filter bubbles"" and ""echo chambers"" and shows how algorithmic power is situated in the interplay between platforms, audiences, and professional communicators. Ultimately, trustworthy algorithms used by news organizations and social media platforms as well as algorithm literacy training are proposed as ways forward towards democratic algorithmic gatekeeping. Presenting a nuanced perspective which challenges the deep divide between techno-optimistic and techno-pessimistic discourse around algorithms, Algorithmic Gatekeeping is recommended reading for journalism and communication researchers in related fields. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.

Details

Language :
English
ISBN :
978-1-03-245072-8
978-1-00-337525-8
978-1-03-245071-1
1-03-245072-X
1-00-337525-1
1-03-245071-1
ISBNs :
9781032450728, 9781003375258, 9781032450711, 103245072X, 1003375251, and 1032450711
Database :
OAPEN Library
Publication Type :
eBook
Accession number :
edsoap.20.500.12657.63155
Document Type :
book
Full Text :
https://doi.org/10.4324/9781003375258