Simulations for novel problems in recommendation: analyzing misinformation and data characteristics
In this position paper, we discuss recent applications of simulation\napproaches for recommender systems tasks. In particular, we describe how they\nwere used to analyze the problem of misinformation spreading and understand\nwhich data characteristics affect the performance of recommendation algorithms\nmore significantly. We also present potential lines of future work where\nsimulation methods could advance the work in the recommendation community.\n