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A User Experience Study on Short Video Social Apps Based on Content Recommendation Algorithm of Artificial Intelligence

机译:基于人工智能内容推荐算法的基于内容推荐算法的用户体验研究

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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.
机译:随着短视频社交应用程序的发展迅速,Feed已成为在此类应用中向用户提交建议内容的主要方法或算法。 视频应用利用基于人工智能算法的饲料流程的方式存在巨大差异。 在本文中使用了用户实验研究了包括Douyin和Kuaishou的两种短视频社交应用程序。 建立了几个指标,以量化这两个应用程序的用户体验差异。 通过相关分析分析结果,以找出用户体验性能与馈送流程的内容呈现模式之间的关系。 结果中发现的差异是从用户认知和行为的角度解释的。

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