The increasing growth of online social platforms such as Facebook, Massive Open Online Courses (MOOCs), and GitHub has provided people with more opportunities to connect, learn, and collaborate. Large activity data streams generated by different parts of an application or across multiple applications allow us to explore in detail the dynamics of user behaviours, which in turn can help to design better support tools and improve their future experience. In MOOCs, for example, almost every interaction between learners and forum threads, wiki pages, or video lectures can be recorded continuously in clickstream data. To understand these learning interactions and hence improve learner engagement, it is important to model dependencies among these clickstream events and utilize them in personalized recommendation tasks. In this talk, we will demonstrate how relational event models can provide us with a methodological framework to achieve these goals, even with complex data sets at the Web scale.