Online popularity can be thought of as analogous to an earthquake; it is sudden, unpredictable, and the effects are severe. While shifts in online popularity are not inherently destructive – consider the unprecedented magnitude of online giving via Twitter following the disaster in Haiti – they indicate radical swings in society’s collective attention. Given the increasingly profound effect that large-scale opinion formation has on important phenomena like public policy, culture, and advertising profits, understanding this behavior is essential to understanding how the world operates.
In this paper by Ratkiewicz and colleagues, the authors put forth a web-wide analysis that includes large-scale data sets of the online behaviors of millions of people. The paper offers a novel model that is is capable of reproducing all of the observed dynamics of online popularity through a mechanism that causes sudden, nonlinear bursts of collective attention. These results have been mentioned in the APS and PhysOrg websites.
I gave four invited talks in Spain, Italy, and Switzerland this summer:
Thanks to my wonderful hosts and their groups for engaging discussions and delightful hospitality!
The aim of this project is to characterize, study and model the sources of bias that emerge from the complex network structure of the Web and from the use of search engines. The feedback loops between users searching information, users creating content, and the ranking algorithms of search engines that mediate between them, lead to surprising results. We are studying how all these systems and communities influence and feed on each other in a dynamic information ecology, and how these interactions affect their evolution and their impact on the global processes of information discovery, retrieval, and utilization.
For example, studying the relationship between Web traffic and PageRank, we have shown that given the heterogeneity of topical interests expressed by search queries, search engines mitigate the popularity bias generated by the rich-get-richer structure of the Web graph. These results, dispelling the feared Googlearchy affect, have been published in Proc. Natl. Acad. Sci. USA, presented at the WAW 2006 keynote (slides), and generated some media attention. You can see some movies demonstrating the finding. The result also inspired a robust rank-based model of scale-free network growth, published in Phys. Rev. Lett. (press release).
We also study sources of bias that stem from legal, political, or economic factors. The CENSEARCHIP tool visualizes the differences between results obtained from different search engines, or different country versions of a search engine. This tool, based on a technique described in this paper in First Monday, generated a lot of reactions in the media and the blogosphere (press release).
Project Participants

Fil Menczer

Sandro Flammini

Alex Vespignani

Santo Fortunato

Mark Meiss
Support
Opinions, findings, conclusions, recommendations or points of view of this group are those of the authors and do not necessarily represent the official position of the National Science Foundation, the Volkswagen Foundation, or Indiana University.