Yuan Hsiao, PhD
Assistant Professor of Sociology
Yuan Hsiao is an Assistant Professor of Sociology at Yale University. He received a PhD in Sociology and MS in Statistics from the University of Washington. He utilizes the training from both disciplines to conduct multi-data and multi-methods research. His major research areas include digital media, social networks, collective behavior, and health. He combines “big” digital data, administrative records, survey experiments, and historical archives to glean insight into these social processes. His research brings a network perspective to understanding questions pertinent to a variety of online and offline social processes. Examples include how networks on social media contribute to political mobilization, how gang members engage in online and offline conflict relationships, how personal relationships affect the spread of religion, or how community networks affect health behavior. Central to all these examples is societal change, such as the rise of social media, reshapes how people form network relationships, and in turn how such network relationships affect collective phenomena such as political mobilization.
What do you do with Data Science?
With the dual degrees of Sociology of Statistics, I apply a variety of statistical methods to understand social phenomena. I especially employ social network analysis in my research, with the central question of: How do we use a network perspective to explain the spread of social behaviors, such as protest attendance, religious participation, or conflict behavior? Using network analysis, I have contributed to answering questions such as how online and offline networks co-produce conflict (American Sociological Review, 2023), how the structure of online networks facilitates or hinders political mobilization (Social Forces, 2021), whether rhetoric of mass media content mirrors the content of user-generated comments (Communication Research, 2024), or how adolescent aggressive behavior spread through peer networks (Social Networks, 2019). Other than network analysis, I frequently use computational and advanced data science methods to inquire social questions such as using Bayesian hierarchical space-time models to estimate migration (Sociological Methods & Research, 2024), using simulations to understand the diffusion of competing behaviors (Journal of Computational Social Science, 2022), using multi-level modeling to evaluate intervention effectiveness (Health & Social Care in the Community, 2022), or using structural equation modeling to explain protest participation (New Media & Society, 2018).