]> 2006-11-13T12:00:00-05:00 2006-11-13T02:00:00-05:00 We propose to study and characterize influence on the Blogosphere by combining many contributing factors, including topic, social structure, opinions, biases and time. Studies on influence in social networks and collaboration graphs have considered a static view of the network and are based purely on link analysis. However, influence on the Web is often a function of topic. We propose the notion of `topical influence' and extend existing techniques to make them topic sensitive. An important component in understanding influence is to detect sentiment and opinions. Changes in opinions, aggregated over many users, can be a predictor for an interesting trend in a community. We describe BlogVox, a testbed blog analytics system that we developed for TREC opinion retrieval task. This system finds opinionated blog posts about a topic. We propose to extend this system to detect bias and to aggregate opinions across communities. Finally, we propose to model influence as a temporal phenomenon. The Blogosphere, being a buzzy and dynamic environment, has new topics emerging constantly and blogs rising and falling in popularity. Tracking these changes over time allows us to find blogs that are influential versus something that is just briefly popular.

We will develop, implement and experimentally evaluate such a model to demonstrate its improved accuracy over models based on any one of these factors alone. ]]>