1. Modeling Trust and Influence in the Blogosphere using Link Polarity
Anubhav Kale et al. (ICWSM 2007)
University of Maryland
Presented by Sai Moturu

2. Introduction
The theme is similar to Nitin’s work but the approach is different
Use links in the blog graph to associate blog-blog link sentiment for a domain
This is called link polarity – has a sign and magnitude based on the sentiment

3. Sentiment detection Analyze text around the link in the source blog
A window of ‘X’ characters before and after
Use a corpus of positive/negative words
Calculating link polarity:

4. Trust Propagation Blog graphs are not always densely connected
A sentiment spread mechanism is needed
Idea from Guha et al., 2004
Distrust is propagated too (not just one-step)

5. Data Buzzmetrics data set Domain: Political Blogs
Over 1.3 million blog posts
Provides link structure between posts
Domain: Political Blogs
Reasonably high link density
Minimal number of off-the-topic posts
Two sets: Republican & Democratic bloggers
300 blogs

6. Classification
A positive score for blog B from the top three democratic blogs (pre-defined) indicates that blog B is Democratic and a negative score indicates that it is Republican

7. Results

8. Conclusions
Novel approach for classifying blogs (observe that the focus shifts from modeling trust and influence)
Preliminary results are promising. Future work will improve upon this