Modeling Trust and Influence on Blogosphere using Link Polarity

There is a growing interest in exploring the role of social networks for understanding how communities and individuals spread influence. The key contribution of our work is generation of a fully-connected polar social network graph from the sparsely connected social network graph in the context of blogs, where the vertex represents a blogger and the weight of an edge in the polar network represents the bias/trust/distrust between its connecting vertices (the source and destination bloggers). Our approach uses the link structure of blog graph to associate sentiments with the links connecting two blogs. We use trust propagation models to spread this sentiment from a subset of connected blogs to other blogs to generate the fully connected polar blog graph. Our experimental validation on determining ""like minded"" blogs on the political blogosphere demonstrates the potential of using polar links for more generic problems such as detecting trustworthy nodes in web graphs.