Breaking the boredom-fatigue cycle: How algorithmic awareness protects against social media exhaustion

This study examines how boredom proneness and information overload contribute to social media fatigue among digitally native young adults (aged 18–30), and how algorithmic media content awareness (AMCA) moderates these relationships. Drawing on the Stress–Strain–Outcome (SSO) framework, survey data from 408 participants were analyzed using structural equation modeling. The findings indicate that boredom proneness functions as a key stressor that increases information overload, which in turn leads to social media fatigue. Information overload partially mediates the relationship between boredom proneness and fatigue, highlighting its role as an important strain mechanism. The results further show that AMCA significantly weakens the effects of boredom proneness on both information overload and social media fatigue, demonstrating a consistent buffering effect across the SSO pathway. Conceptually, the study extends the SSO framework by introducing AMCA as a digital literacy–based cognitive resource that helps individuals better interpret and manage algorithmically curated content environments. By foregrounding the role of algorithmic awareness, this research offers new insights into digital well-being and identifies algorithmic literacy as a promising intervention for reducing fatigue among boredom-prone young adults in algorithmically mediated social media contexts. • Boredom proneness drives information overload and social media fatigue in young adults. • Algorithmic Media Content Awareness (AMCA) buffers boredom-driven digital exhaustion. • AMCA's protective effect is strongest early in the stress-strain-outcome pathway. • Information overload partially mediates the boredom-fatigue relationship, serving as critical strain mechanism. • Higher algorithmic literacy empowers users to recognize filter bubbles and regulate social media consumption proactively.