Paper Info
Title
The effectiveness of user-centric social interfaces on evaluating mobile recommendations.
Abstract
Many studies on recommender systems have focused on increasing their accuracy by enhancing the algorithms employed. Social perceptions, however, influence both satisfaction and perceived accuracy of mobile recommender systems. Thus, the aim of this study was to investigate the importance of including reasons for particular recommendations by examining the role of social presence and self-reference and their effects on user evaluations of mobile recommender systems. We performed a 2 x 2 experimental setting (Four experimental web pages with user-to-user and item-to-item collaborative filtering) which was used to manipulate customer perception of accuracy through social presence and self-reference. Social presence and self-reference were shown to be antecedents of perceived accuracy of mobile recommender systems. Additionally, perceived accuracy appeared to be a partial mediator of the relationship between social presence and satisfaction, whereas perceived accuracy appeared to be a full mediator of the relationship between self-reference and satisfaction.
Year
DOI
Venue
2016
10.1145/2971603.2971622
ICEC
Field
DocType
Citations 
Recommender system,Collaborative filtering,Web page,Computer science,Knowledge management,Self-reference,Social interfaces,Perception,User-centered design,Personalization
Conference
0
PageRank 
References 
Authors
0.34
25
2
Name
Order
Citations
PageRank
Jaewon Choi19211.74
Hong Joo Lee225921.05