A Survey of Graph Neural Networks for Social Recommender Systems
Georgia Institute of Technology · Ulsan National Institute of Science and Technology · +1 more institution
Abstract
Social recommender systems (SocialRS) simultaneously leverage the user-to-item interactions as well as the user-to-user social relations for the task of generating item recommendations to users. Additionally exploiting social relations is clearly effective in understanding users’ tastes due to the effects of homophily and social influence. For this reason, SocialRS has increasingly attracted attention. In particular, with the advance of graph neural networks (GNN), many GNN-based SocialRS methods have been developed recently. Therefore, we conduct a comprehensive and systematic review of the literature on GNN-based SocialRS. In this survey, we first identify 84 papers on GNN-based SocialRS after annotating…
Citation impact
- FWCI
- 137.21
- Percentile
- 100%
- References
- 125
Authors
7Topics & keywords
- Computer science
- Recommender system
- Graph
- Artificial neural network
- Artificial intelligence
- Information retrieval
- Data science
- Theoretical computer science
- Reduced inequalities