Connecting Perceived Worthwhileness to News Consumption Patterns and Algorithm Recommendations on Chinese Social Media Bilibili

This study examines how young Chinese adults perceive the worthwhileness of news on Bilibili, a short-video social media platform, and how algorithmic recommendation systems influence their news consumption habits. Through in-depth interviews with 33 users aged 20–30, three distinct user typologies emerged: passive, moderate, and active. Each group engages with Bilibili’s news differently, shaped by specific dimensions of perceived worthwhileness—dimensions of “public connection” and “participatory potential” are closely connected to active news consumers, while the dimension of “normative pressure” is closely linked to passive news consumers. Algorithmic personalization both streamlines and constrains news exposure, raising concerns about filter bubbles and epistemic justice. Findings extend Schrøder’s framework to a non-Western context and propose implications for digital literacy, algorithmic transparency, and civic participation.