The Web Dynamics group works to build a better understanding of how the Web, the Wikipedia, and similar large information networks, grow and change over their lifetime. Of particular interest is how nodes in these networks gain popularity.

This work has leveraged data from the Wikimedia project, as well as from Mark Meiss, concerning traffic to Wikipedia pages and pages in the Internet at large.

Our preliminary work has painted a picture of the Web as a place in which popularity is very dynamic and unpredictable. Surges in popularity for topics are similar to earthquakes and avalanches in terms of their unpredictability — both in when they will happen and on what scale. However, we find that spikes in popularity are often correlated with events in the news — as evidenced by positive correlation between Google Trends data and traffic to bursty Wikipedia topics. Work on this project has been presented at SocialCom 2010 Symposium on Social Intelligence and Networking (SIN-10). A review of these issues with an emphasis on the modeling problem was also published in Physical Review Letters.

Further research is focused on modeling — and predicting — popularity bursts, as well as exploration of other networks and sources of data, such as Twitter.

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