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

被引：8
|
作者：
Qi, Wen [1 ]
Li, Danyang [1 ]
机构：
[1] Donghua Univ, Dept Prod Design, Shanghai 200051, Peoples R China
来源：
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2021年 / 35卷 / 02期
关键词：
Short video social app; recommendation system; machine learning; feed flow; user experience; correlation analysis;
D O I：
10.1142/S0218001421590084
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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收藏
页数：13
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