Everyday-Inspired Movies: Towards the Design of Movie Recommender Systems based on Everyday Life through Personal Social Media

被引:0
作者
Kulkarni, Abhishek [1 ]
Powell, Larry [2 ]
Murphy, Shaina [1 ]
Rao, Nanjie [1 ]
Chu, Sharon Lynn [1 ]
机构
[1] Univ Florida, Gainesville, FL 32611 USA
[2] Texas A&M Univ, College Town, TX 77843 USA
来源
HUMAN-COMPUTER INTERACTION - INTERACT 2023, PT III | 2023年 / 14144卷
关键词
Movie Recommender Systems; Social Media; Everyday Life; Personalized Recommendations;
D O I
10.1007/978-3-031-42286-7_9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes the idea of movie recommenders that draw from the users' everyday life happenings as documented through their personal social media posts to produce relevant recommendations. We conducted an experimental study to understand the important dimensions to consider in the design of such a recommendation system. We began with the design hypothesis that matching keywords and categories from users' social media posts to those from movie plots may increase users' perceived relevance of movie recommendations. Our analysis revealed that beyond keywords and categories, emotional context and genre of movies are important aspects to consider. Based on these findings, we discuss the implications on the design of movie recommendation systems leveraging users' everyday life through social media posts.
引用
收藏
页码:160 / 169
页数:10
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