In this paper, we develop a simple model to study and analyze communication dynamics in the blogosphere and use these dynamics to determine interesting correlations with stock market movement. This work can drive targeted advertising on the web as well as facilitate understanding community evolution in the blogosphere. We describe the communication dynamics by several simple contextual properties of communication, e.g. the number of posts, the number of comments, the length and response time of comments, strength of comments and the different information roles that can be acquired by people (early responders / late trailers, loyals / outliers). We study a "technology-savvy" community called Engadget (http://www.engadget.com). There are two key contributions in this paper: (a) we identify information roles and the contextual properties for four technology companies, and (b) we model them as a regression problem in a Support Vector Machine framework and train the model with stock movements of the companies. It is interestingly observed that the communication activity on the blogosphere has considerable correlations with stock market movement. These correlation measures are further crossvalidated against two baseline methods. Our results are promising yielding about 78% accuracy in predicting the magnitude of movement and 87% for the direction of movement.
Choudhury et al. REF develop a model analyzing communication dynamics in the blogosphere to decide correlations with movement in stock market.
Can blog communication dynamics be correlated with stock market activity?
HT '08
Computer Science