A study on the exposure of contemporary 12-year-old adolescents to age-inappropriate online content: prevalence and risks

Twelve-year-old adolescents are in a critical transitional phase of cognitive development, marked by underdeveloped worldviews and limited capacity to discern and resist complex information. In today's digital landscape, the ease of information dissemination and blurred boundaries often expose this demographic to "age-inappropriate" contentincluding adult-themed topics and developmentally mismatched discoursethrough passive engagement with social platform recommendation algorithms. Current governance of youth-oriented online content predominantly focuses on explicit harmful material, while the identification and intervention of implicit age-inappropriate content remain inadequate, failing to effectively safeguard adolescents' digital growth. As internet penetration deepens among younger users, the boundaries of information exposure become increasingly ambiguous, sparking societal concerns about psychological "precocity." This study employs empirical methods to investigate the prevalence of age-inappropriate online content exposure among 12-year-olds. Using Sina Weibo as a case platform, Python-based web scraping collected user content, and a Bayesian classifier trained on adolescent health-related datasets was applied to classify content into "appropriate" and "inappropriate" categories. By analyzing the sample accounts, this research aims to assess the extent of "precocity risk." The findings are expected to provide data-driven insights for enhancing digital literacy education and improving online content governance.