The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification

We present a new, intuitive semi-supervised learning algorithm for classifying political blogs in a blog network and ranking them within classes. In the algorithm each link is assigned a label as well as the blogs. Using only the link structure as input and by exploiting the linking properties found in political blog communities, we bootstrap the classification of links and blogs and blog rankings from a set of known seed blogs. We test our algorithm on two datasets and achieve blog classification accuracy of 81.9% in a network of 404 blogs and 84.6% in a network of 1222 blogs using only 2 seed blogs in each case. We analyze the results our algorithm and show that the misclassifications tend to be less important or less authoritative blogs.