Modeling Trust and Influence in Blogosphere using Link Polarity

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Abstract: The role of social networks has been well explored in understanding how communities and individuals spread influence. In a densely connected world where much of our communication happens online, social media and networks have a great potential in influencing our thoughts and actions. We describe techniques to find "like minded" blogs based on blog-to-blog link sentiment for a particular domain. Using simple sentiment detection techniques, we identify the polarity (positive, negative or neutral) of the text surrounding links that point from one blog post to another. We use trust propagation models to spread this sentiment from a subset of connected blogs to other blogs and deduce likeminded blogs in the blog graph. Our results confirm that the simple heuristics for analysis of text surrounding links and generation of missing polar links (links with positive or negative sentiment) using trust propagation is highly applicable for domains having weak link structure. These techniques demonstrate the potential of using polar links for more generic problems such as detecting trustworthy nodes in web graphs.

Type: MastersThesis

Tags: blog, influence, link polarity, trust

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