Making Sense of Imperfectly Observed Networks
Johan Koskinen - Lecturer in Statistics at Stockholm University - presented the seminar "Making Sense of Imperfectly Observed Networks" at the ANU School of Sociology. The presentation covered some of the research projects he has been involved, with a focus on network data and statistical methods used to understand link-formation processes and the effects of networks on behaviour and attitudes. The author covered the challenges - both conceptual as well as technical - with analysing networks obtained in difficult circumstances in the context of a number of different empirical examples, and discussed approaches to overcome incomplete network data, that afford such imperfections.
The seminar took place on 8 March 2023, and it was co-hosted by the VOSON Lab, ANU School of Sociology and the ANU School of Politics and Inernational Relations (SPIR).
Johan Koskinen is Lecturer in Statistics at Stockholm University, having previously held positions at the Universities of Melbourne, Oxford, and Linkoping. He develops statistical models and inference for social networks and often works in close collaboration with subject area experts to infer underlying network processes for empirical data, preferably within a Bayesian framework. Together with colleagues in Melbourne he put together the 2013 book on Exponential Random Graph Models, which was awarded the Harrison White Book Award. He has contributed to the publicly available programs MPNet and RSiena, and has been active in delivering training in network analysis across the world. Of particular interest to him, is imperfectly observed network data and computational methods for networks on different types of ties and nodes, in space and across time.
Photo by Omar Flores on Unsplash