Children’s sensemaking of algorithms and data flows across YouTube and social media

Abstract

Purpose This study aims to explore children’s cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own device and use social media and YouTube, despite platform age requirements. Design/methodology/approach Nine focus groups with 34 socioeconomically, racially and ethnically diverse children (8–11 years) were conducted in California. Groups discussed data flows online, digital privacy, algorithms and personalization across platforms. Findings Children had several misconceptions about privacy risks, privacy policies, what kinds of data are collected about them online and how algorithms work. Older children had more complex and partially accurate theories about how algorithms determine the content they see online, compared to younger children. All children were using YouTube and/or social media despite age gates and children used few strategies to manage the flow of their personal information online. Practical implications The paper includes implications for digital and algorithmic literacy efforts, improving the design of privacy consent practices and user controls, and regulation for protecting children’s privacy online. Originality/value Research has yet to explore what socioeconomically, racially and ethnically diverse children understand about datafication and algorithms online, especially in middle childhood.