Peter Martin Krafft

Peter Krafft

I am a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington, where I work with Emma Spiro in the Information School's DataLab and co-direct the Critical Platform Studies Group. I am also a part-time postdoctoral researcher with Tom Griffiths at the University of California Berkeley's Social Science Matrix, and I recently spent a little time as a visiting postdoctoral scholar working with Joan Donovan at the Data & Society Research Institute in New York City. Previous to being an itinerant postdoc, I completed my PhD at MIT, where I was co-advised by Sandy Pentland and Josh Tenenbaum in EECS, CSAIL, the Media Lab, and the Department of Brain and Cognitive Sciences. I was also once a Master's student at UMass Amherst with Hanna Wallach, and an undergraduate researcher at UMass with Andy Barto and separately with Michael Lavine.

In my research I develop new social data analysis methods to better understand rumors, fads, disinformation, and information flow. The predominant theoretical lenses I deploy in my work are the perspectives of modern computational cognitive science, organization science's theorizing of collective intelligence, and the classical social psychology and sociology literatures on rumors. The methods I have developed span the areas of observational data analysis, structured behavioral modeling, online laboratory experimentation, and online field experimentation. Several of my research projects have specific implications that could inform pressing policy issues, such as the development of systems for dealing with certain types of misinformation; the design of online financial exchange platforms; and ethical approaches to social data science.

The problems I am most keen on thinking about in the coming years are: (1) rumors, (2) the sociology of knowledge, (3) the design of digital institutions, (4) value distribution, (5) political theory, (6) distributed inference.