Clarifying the relationship mechanism between perceived algorithmic recommendation accuracy and user satisfaction helps platforms optimize recommendation algorithms in a targeted manner and guide algorithms to be bene...Clarifying the relationship mechanism between perceived algorithmic recommendation accuracy and user satisfaction helps platforms optimize recommendation algorithms in a targeted manner and guide algorithms to be benevolent.Based on the Stimulus-Organism-Response(S-O-R)theory,this study constructs a theoretical model of how perceived algorithmic recommendation accuracy affects user satisfaction on short video platforms.By analyzing 398 valid questionnaires,the conclusions are drawn as follows:First,there is an inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction,which first increases and then decreases;second,algorithm fatigue plays a mediating role in the inverted Ushaped relationship between perceived algorithmic recommendation accuracy and user satisfaction;third,information-seeking motivation moderates the inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction.展开更多
文摘Clarifying the relationship mechanism between perceived algorithmic recommendation accuracy and user satisfaction helps platforms optimize recommendation algorithms in a targeted manner and guide algorithms to be benevolent.Based on the Stimulus-Organism-Response(S-O-R)theory,this study constructs a theoretical model of how perceived algorithmic recommendation accuracy affects user satisfaction on short video platforms.By analyzing 398 valid questionnaires,the conclusions are drawn as follows:First,there is an inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction,which first increases and then decreases;second,algorithm fatigue plays a mediating role in the inverted Ushaped relationship between perceived algorithmic recommendation accuracy and user satisfaction;third,information-seeking motivation moderates the inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction.
