Arjen van Dalen is Professor WSR at the Center for Journalism of the University of Southern Denmark. He wrote his PhD dissertation on Political Journalism in Comparative Perspective and is co-author of an award-winning book on this topic with Cambridge University Press. He published in journals such as Political Communication, Journalism, the International Journal of Press/Politics, and Public Opinion Quarterly. His research on algorithmic gatekeeping is funded by the Independent Research Fund Denmark and Carlsberg Foundation.

List of Figures

List of Tables

Acknowledgments

Chapter 1: Introduction

1.1 Algorithmic power

1.2 Conceptualizing algorithmic gatekeeping

1.3 Technological determinism, hard and weak

1.4 Theoretical considerations

1.5. Legitimacy and trust

1.6 Outline and Content of the Book

Chapter 2: Algorithm Aversion

2.1 Introduction

2.2 Making sense of news algorithms

2.3 Research questions

2.4 Method

2.5 Results

2.6 Conclusion

Chapter 3: The Mediating Power of Algorithms

3.1 Introduction

3.2 Misinformation and algorithms

3.3 YouTube and Autism Spectrum Disorder

3.4 The mediating power of YouTube's algorithms

3.5 Research questions

3.6 Method

3.7 Results

3.8 Conclusion

Chapter 4: Structuring Power

4.1 Introduction

4.2 Influencers: politically relevant strategic actors

4.3 Algorithmic power

4.3 Research questions

4.4 Method

4.5 Results

4.6 Conclusion

Chapter 5: Algorithmic Power, Trust and Legitimacy

5.1 Algorithmic power

5.2 Algorithms, trust and legitimacy

5.3 Implications

References

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.