Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation
arXiv:2110.00811v1
Originality Synthesis-oriented
AI Analysis
It addresses methodological gaps in recommender systems research for researchers, but is incremental as a position paper without new results.
The paper proposes using simulation to study various aspects of recommender system behavior beyond effectiveness, identifying specific research types and a hierarchy of simulation types.
Recommender systems research is concerned with many aspects of recommender system behavior and effects than simply its effectiveness, and simulation can be a powerful tool for uncovering these effects. In this brief position paper, I identify specific types of research that simulation is uniquely well-suited to address along with a hierarchy of simulation types.