Title: Joint Modeling of Dynamic Social Network Data Collected Online and Offline with an Application to Friendship and Social Media Ties

Abstract: We present a novel statistical model for the joint analysis of temporal social network data collected as digital traces (online data) as well as through surveys (offline data). The model can thereby combine behavioral and cognitive measures of social ties and enable hypothesis tests on the co-evolution of online and offline processes. A new estimation routine addresses the challenge of observing online and offline data at different frequencies, building on the expectation-maximization algorithm. We apply the framework in an empirical study of an emerging community of first-year undergraduate students at a Swiss university. We combine repeated survey measures of friendship perceptions with time-stamped social media connections collected through the Facebook API. This is joint work with Maria Eugenia Gil-Pallares and Viviana Amati.

Bio: Christoph Stadtfeld is Associate Professor of Social Networks at ETH Zürich and co-director of the ETH Social Networks Lab. His research focuses on the dynamics of social network. It addresses questions about how individuals form social ties with one another, how they are affected by the evolving social networks they are embedded in, and how such processes can be studied with new data and statistical methods. Together with his team, he publishes articles in sociological, methodological, and interdisciplinary journals. Christoph received the Raymond Boudon Award of the European Academy of Sociology in 2017 and the Freeman Award of the International Network for Social Network Analysis in 2021. He is a member of the editorial board of Network Science. Christoph Stadtfeld holds a PhD from Karlsruhe Institute of Technology (2011). He has been postdoctoral researcher and Marie-Curie fellow at the University of Groningen, the University of Lugano, and the MIT Media Lab (2011-2014) prior to joining ETH Zurich.