Modeling User Arguments, Interactions, and Attributes for Stance Prediction in Online Debate Forums Supplementary Document

We propose an integrated model to jointly model user arguments, interactions and attributes for the task of stance prediction. The graphical representation of the model can be found in Figure 1. The model is composed of four parts: i.) user profiling, which considers a regression-based latent factorization method to incorporate user attributes for profiling users; ii.) user stance, which contains a binomial matrix factorization method for modeling categorical stance data; iii.) user arguments, which incorporate textual cues in threaded posts; and iv.) user interaction, which integrates the positive and negative interaction attributes between users.