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News Recommendation and Information Cocoons: The Impact of Algorithms on News Consumption

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Handbook of Applied Journalism

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Abstract

This chapter examines algorithmic news recommendation that caters to individual preferences. It aims to illuminate the renewed relationship between media and news audience with algorithmic processes and to explore the impact that such a relationship entails. The chapter dissects the phenomenon of algorithm-based news recommendation and analyzes the effects that algorithmic news consumption may have on audiences. It intends to raise awareness and inform the public, technocrats, and policy makers of the impact of such news consumption and guide debate on ethical decision-making and possible policy change.

This chapter reuses some of the content in the author’s 2023 book “Algorithmic Audience in the Age of Artificial Intelligence,” published by Peter Lang (https://www.peterlang.com/document/1282554), with the copyright clearance granted by the original publisher.

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Notes

  1. 1.

    https://www.statista.com/topics/1640/news/

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Author information

Authors and Affiliations

  1. California State University, Fullerton, CA, USA

    Roselyn Du

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  1. Roselyn Du
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Correspondence to Roselyn Du .

Editor information

Editors and Affiliations

  1. College of Communication, University of Sharjah, Sharjah, United Arab Emirates

    Leon Barkho

  2. College of Communication, University of Sharjah, Sharjah, United Arab Emirates

    Jairo Alfonso Lugo-Ocando

  3. School of International Communications, University of Nottingham Ningbo China, Ningbo, China

    Sadia Jamil

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Du, R. (2024). News Recommendation and Information Cocoons: The Impact of Algorithms on News Consumption. In: Barkho, L., Lugo-Ocando, J.A., Jamil, S. (eds) Handbook of Applied Journalism. Springer Handbooks of Political Science and International Relations. Springer, Cham. https://doi.org/10.1007/978-3-031-48739-2_4

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