Research on the Construction of Aesthetic Communities Based on Intelligent Recommendation Mechanisms in the Social Media Context: A Case Study of Short Video Visual Content
Abstract
With the rapid growth of short video platforms, applications such as Douyin and Kuaishou have become major channels for information and visual content via algorithmic recommendation. In this process, recommendation systems track users' viewing patterns and personalize content delivery based on individual preferences. By using user profiling and collaborative filtering, recommendation systems consolidate existing preferences, limit exposure to varied content, and also promote the emergence of stable aesthetic communities. Based on the theory of aesthetic taste, reception aesthetics and the S-O-R model, this paper analyzes the formation mechanism and impacts of aesthetic circlization in short videos. The study suggests that the phenomenon results from the combined influence of algorithmic distribution mechanisms, user preference feedback, and social identity processes. In turn, this process accelerates the circulation of specific content and strengthens community interaction, while also increasing content convergence, narrowing aesthetic diversity, and deepening differentiation between communities. Accordingly, this study proposes strategies from four dimensions: algorithm optimization, platform governance, user media literacy improvement, and multi-stakeholder collaboration.
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