In an algorithmically curated media environment, passive modes of news consumption have become increasingly prevalent, raising growing concerns about news avoidance. Focusing on Chinese Gen Z, this study examines the cognitive dimension of passive news consumption through the lens of the news finds me (NFM) perception. It develops an analytical framework incorporating algorithmic recommendation dependence, news fatigue, and fear of missing out (FOMO) to investigate the underlying mechanisms linking passive news consumption to news avoidance. Drawing on survey data (N = 278), the results show that NFM perception does not exert a direct significant effect on news avoidance. Instead, its influence operates indirectly through a sequential mediation pathway involving algorithmic recommendation dependence and news fatigue. Furthermore, FOMO positively moderates the relationship between news fatigue and news avoidance, amplifying the effect of fatigue on avoidance behavior. These findings suggest that news avoidance among Chinese Gen Z is less a direct consequence of passive exposure and more a result of the cumulative psychological burden generated within algorithm-driven information environments. This study contributes to the literature by clarifying the cognitive and affective mechanisms underlying news avoidance in the context of algorithmic news ecosystems.

Xu Xiaoting, Hong Zhou. A Sequential Mechanism Linking Algorithmic Dependence and News Fatigue. Academic Journal of Humanities & Social Sciences (2026), Vol. 9, Issue 5: 59-72. https://doi.org/10.25236/AJHSS.2026.090509.

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