Algorithmically structured exposure: Adolescents’ emotional experiences of content types on social media

Background: Research on social media and young people’s mental health has focused on screen time, with less attention to the types of content encountered within algorithmically curated feeds. Evidence suggests different content types may have distinct implications, yet young people’s perspectives remain underexplored.Methods: Semi-structured interviews were conducted with 27 UK adolescents aged 14-19. Using photo-elicitation, participants shared screenshots from TikTok ‘For You’ or Instagram ‘Explore’ pages. Data were analysed using reflexive thematic analysis.Results: Participants described diverse content types (e.g., entertainment, consumerism, identity, mental health, news, body image, AI-generated), all experienced as double-edged. Perceived impacts depended on repeated exposure shaped by algorithms and individual context, with greater perceived risk linked to low mood, younger age, and lower literacy.Conclusions: Findings highlight how algorithmic curation structures repeated exposure across content types, shaping how experiences accumulate and are interpreted over time.Key words: Algorithmic recommendation; Adolescents; Social media content; Wellbeing; Mental health; Photo-elicitation; Qualitative research