Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media

Abstract

The news that young people consume is increasingly subject to algorithmic curation. Yet, while numerous studies explore how algorithms exert power in citizens’ everyday life, little is known about how young people themselves perceive, learn about, and deal with news personalization. Considering the interactions between algorithms and users from an user-centric perspective, this article explores how young people make sense of, feel about, and engage with algorithmic news curation on social media and when such everyday experiences contribute to their algorithmic literacy. Employing in-depth interviews in combination with the walk-through method and think-aloud protocols with a diverse group of 22 young people aged 16–26 years, it addresses three current methodological challenges to studying algorithmic literacy: first, the lack of an established baseline about how algorithms operate; second, the opacity of algorithms within everyday media use; and third, limitations in technological vocabularies that hinder young people in articulating their algorithmic encounters. It finds that users’ sense-making strategies of algorithms are context-specific, triggered by expectancy violations and explicit personalization cues. However, young people’s intuitive and experience-based insights into news personalization do not automatically enable young people to verbalize these, nor does having knowledge about algorithms necessarily stimulate users to intervene in algorithmic decisions.