A simple generative model of collective online behavior

• DOI: 10.1073/pnas.1313895111
• Publication Date: 2014-07-08T03:01:33Z
• Authors: James P. Gleeson; Davide Cellai; Jukka-Pekka Onnela; Mason A. Porter; Felix Reed-Tsochas
• Keywords: Social and Information Networks (cs.SI); FOS: Computer and information sciences; 0301 basic medicine; Physics - Physics and Society; Internet; FOS: Physical sciences; Computer Science - Social and Information Networks; Physics and Society (physics.soc-ph); Models, Theoretical; 01 natural sciences; Social Networking; 03 medical and health sciences; 0103 physical sciences; Humans; Cooperative Behavior

Significance One of the most common strategies in studying complex systems is to investigate and interpret whether any “hidden order” is present by fitting observed statistical regularities via data analysis and then reproducing such regularities with long-time or equilibrium dynamics from some generative model. Unfortunately, many different models can possess indistinguishable long-time dynamics, so the above recipe is often insufficient to discern the relative quality of competing models. In this paper, we use the example of collective online behavior to illustrate that, by contrast, time-dependent modeling can be very effective at disentangling competing generative models of a complex system.