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Algorithmic Audience in the Age of Artificial Intelligence employs
a mix-methods approach to examine and interpret the algorithmic
news consumption phenomenon from several inter-related
perspectives, including tailored communication, customization,
gatekeeping, agenda-resisting, and news literacy. Potential
implications for an empowered or rather, (information-) cocooned
public are explored. The research aims to illuminate the renewed
relationship between media and audience and the effects on users of
algorithmic processes. The aim of the book is multifaceted: (1) to
describe the phenomenon of AI-based news recommendation; (2) to
explore the use experience of consuming recommended news; (3) to
analyze the effects that algorithmic news consumption has on the
audiences; (4) to raise awareness of the impact of algorithmic news
consumption; (5) to inform the public, technocrats, and policy
makers of the effects of algorithmic news consumption; (6) to guide
debate on ethical decision-making and possible policy change.
Through an empirical investigation process, this volume examines
algorithmic news consumption from a user perspective and dissects
the complex effects caused by such consumption. This book is
suitable to be a primary text for undergraduate-level courses
relating media literacy issues and graduate-level courses with a
particular focus on audience analysis in the age of artificial
intelligence. It can also serve as a supplemental text for a core
course in media/communication studies, such as Introduction to
Communication, Current Issues in Communication, Communication
Theory, Communication Ethics, etc. Worldwide.
Algorithmic Audience in the Age of Artificial Intelligence employs
a mix-methods approach to examine and interpret the algorithmic
news consumption phenomenon from several inter-related
perspectives, including tailored communication, customization,
gatekeeping, agenda-resisting, and news literacy. Potential
implications for an empowered or rather, (information-) cocooned
public are explored. The research aims to illuminate the renewed
relationship between media and audience and the effects on users of
algorithmic processes. The aim of the book is multifaceted: (1) to
describe the phenomenon of AI-based news recommendation; (2) to
explore the use experience of consuming recommended news; (3) to
analyze the effects that algorithmic news consumption has on the
audiences; (4) to raise awareness of the impact of algorithmic news
consumption; (5) to inform the public, technocrats, and policy
makers of the effects of algorithmic news consumption; (6) to guide
debate on ethical decision-making and possible policy change.
Through an empirical investigation process, this volume examines
algorithmic news consumption from a user perspective and dissects
the complex effects caused by such consumption. This book is
suitable to be a primary text for undergraduate-level courses
relating media literacy issues and graduate-level courses with a
particular focus on audience analysis in the age of artificial
intelligence. It can also serve as a supplemental text for a core
course in media/communication studies, such as Introduction to
Communication, Current Issues in Communication, Communication
Theory, Communication Ethics, etc. Worldwide.
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