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With short-video platforms deeply integrated into the daily lives of older adults, the attention-economy model based on algorithmic recommendations boosts user stickiness while creating fraud risks targeting elderly users. Taking Douyin as an example, this paper introduces three core concepts: filter bubbles, echo chambers and attention bubbles, to explore how algorithmic mechanisms construct closed, high-risk information environments through traffic orientation and content distribution. According to the latest statistics, China’s internet users aged 60 and above have exceeded 150 million, among whom over 80% use short-video platforms. However, the fraud victimization rate of this group is 2.5 times the national average online rate. The study finds that algorithms favor highly emotional content, forming attention bubbles. Repeated delivery of homogenized information creates filter bubbles and echo chambers. The resonance between these two mechanisms and older adults’ media habits and cognitive weaknesses significantly raises their risk of being scammed. Accordingly, this paper proposes a multi-stakeholder collaborative governance framework combining family emotional intervention, platform algorithmic benevolence and government regulatory constraints.
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Yangfanyu Zeng (2026) studied this question.
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