Predicting Response to Political Blog Posts with Topic Models

In this paper we model discussions in online political weblogs (blogs). To do this, we extend Latent Dirichlet Allocation, introduced by Blei et al. (2003), in various ways to capture different characteristics of the data. Our models jointly describe the generation of the primary documents (“posts”) as well as the authorship and, optionally, the contents of the blog community’s verbal reactions to each post (“comments”). We evaluate our model on a novel “comment prediction” task where the models are used to predict comment activity on a given post. We also provide a qualitative discussion about what the models discover.