Riley Crane (born 1977) works on projects which try to uncover the hidden patterns governing individual and collective activity. His projects seek to understand very generally how information spreads.
He is the Society in Science (Branco Weiss) senior postdoctoral fellow in the Human Dynamics Group, at the Media Lab at M.I.T. His research is focused on understanding the hidden patterns behind collective social behavior. A physicist by training, he has spent the last several years quantifying human behavior and social interactions, and has applied his models to diverse systems such as YouTube and the humanitarian response to the Asian Tsunami. Riley is the winner of the 2009 DARPA Network Challenge, a Pentagon sponsored competition aimed at exploring the roles the Internet and social networking play in the timely communication, wide-area team-building, and urgent mobilization required to solve broad-scope, time-critical problems. In addition to his scientific work he consults for business and government and has started several companies, which harness the power of social networks and social media and has built viral media campaigns for books and the United Nations. His work has been featured in newspapers and magazines such as The New York Times, New Scientist, and on television including CNN and The Colbert Report.
The past few decades have witnessed impressive growth in our understanding of individual human activity on the one hand, and collective effects in networks on the other. Detailed investigations into the timing of individual activity have revealed that actions ranging from sending email to trading stocks to checking out library books, once thought to be randomly occurring in time with weak periodicity, are in fact highly correlated, with non-trivial dynamics characterized by bursts of activity followed by long pauses. At the same time the science of networks has revealed the dramatic impact that network structure can have on shaping collective decision processes and the dynamics of contagion processes such as the spread of disease or the diffusion of technology and ideas. In spite of these advances, very little work has successfully shown how collective, global behavior emerges from the aggregation of local, individual activities in social, biological and economic contexts. However, overcoming this divide is of central importance if we are to understand the sudden bursts of activity that frequently occur in these systems when seemingly random individual activity becomes synchronized as a result of spreading and interactions – from social unrest to best-selling books sales, financial crashes and pandemic influenza.
He is therefore interested in whether or not there are rules governing collective behavior that can be shown to arise from a detailed understanding of individual activity. Additionally, He is interested in developing tools and methodologies for harnessing the vast potential of the human network.