Douglas Guilbeault studies computational social science with Damon Centola in the Network Dynamics Group. He uses formal models and online experiments to study political communication and cultural evolution. His recent study in the Proceedings of the National Academy of the Sciences shows how communication in bipartisan networks can reduce polarization via collective intelligence, but that this polarization is maintained if people are primed to process information in terms of political social categories (e.g. party membership). His dissertation explores how social categories emerge in the first place, using a series of online experiments involving the dynamic construction of category systems in social networks.
Guilbeault also engages in policy-related research surrounding social media. In a recent article in the journal of Policy & Internet, he provides an overview of the policy issues created by emerging misinformation technologies such as bots – a topic he has elsewhere discussed in the International Journal of Communication. Guilbeault has also written several journalistic pieces on these topics for outlets including The Atlantic and Wired. This research is supported by collaboration with members of the Computational Propaganda Project at the Oxford Internet Institute.
Guilbeault's research is funded by a Joseph-Armand Bombardier doctoral scholarship from the Social Sciences and Humanities Research Council of Canada, and by a dissertation fellowship from the Institute for Research on Innovation and Science.