As short video social apps develop rapidly, feed has become the main approach or algorithm to present recommendation content to users in such apps. There are big differences in the way that video apps make use of feed flow based on artificial intelligence algorithm. Two kinds of short video social apps including DouYin and KuaiShou are studied with a user experiment in this paper. Several indicators are established to quantify the user experience differences of these two apps. The results are analyzed with correlation analysis to find out the relationship between user experience performance and content presentation mode of feed flow. The differences found from the results are explained from the perspectives of user cognition and behavior.

中文翻译：

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基于人工智能内容推荐算法的短视频社交应用用户体验研究

随着短视频社交应用的快速发展，Feed 已成为此类应用中向用户呈现推荐内容的主要方式或算法。视频应用程序使用基于人工智能算法的 Feed 流的方式存在很大差异。本文通过用户实验研究了抖音和快手两种短视频社交应用。建立了几个指标来量化这两个应用程序的用户体验差异。对结果进行相关性分析，找出用户体验表现与Feed流的内容呈现方式之间的关系。从用户认知和行为的角度解释了从结果中发现的差异。