Relational event models for social learning in MOOCs

Abstract

We propose three extensions for the relational event framework to model the co-evolution of multiple network event streams which are increasingly available thanks to the explosive growth of online applications. Firstly, a flexible stratification approach is considered to allow for more complex data structures with many types of nodes and events. Secondly, an inference method that combines nested case-control sampling with stratification is discussed to scale the approach to very large data sets. Finally, a suite of new temporal and network statistics is introduced to reflect the potentially complex dependencies among events and observed heterogeneities on nodes and edges.The empirical value ..