Research on digital money, platform governance and online interaction, and on computational methods for social science.

What we study. This cluster examines the social effects of digital infrastructure, data and artificial intelligence, and develops the computational methods used to study them. Work in the cluster covers digital money, blockchain and Web3; platform governance and the administration of online markets; online interaction, new media and the norms people bring to digital settings; the effects of automation on work and status; the quantification of conduct in state and commercial scoring systems; and computational methods including network analysis, digital trace data and causal inference. The cluster covers both AI and digital technology as objects of sociological study, and computational social science as a way of doing sociology.

Recent work. Tom McDonald holds two GRF grants, on Hong Kong’s Web3 visions and on Chinese podcasting cultures, and has published in Platforms & Society, The Information Society and Economy and Society. Isak Ladegaard’s Open Secrecy: How Technology Empowers the Digital Underworld appeared in 2025. Benjamin Rohr uses computational and network methods on historical political data, most recently in the American Sociological Review (2025). Lai Wei works on causal inference and computational social science, with papers in Sociological Methods & Research (2025, 2026). Guy Abel applies machine learning and digital trace data to migration estimation. Cheris Chan’s current project examines China’s social credit system. Two Common Core courses developed in the Department take these questions to undergraduates: “AI & Web3: Social Futures of Decentralised Artificial Intelligence” and “Real Harm in an Unreal World: Crime, Regulation and AI”.

This cluster is the Department’s home for the Faculty’s AI, Society and Social Dynamics theme, co-led by Professor Duoduo Xu.