Methods
The methods cluster brings together faculty and students with a shared interest in traditional sociological methods and newly emerging computational social science methods. Members in the cluster seek to employ and improve these methods by integrating social dimensions with spatial dimensions to address substantive social science problems. The blending of small data from social surveys or field experiments with large-scale data from social media, dynamic networks, mobility trajectories, and social simulations to provide new sociological insights is encouraged.
This cluster will work closely with the Computational Social Science Laboratory in Faculty of Social Science to run seminars/webinars with speakers from the academy and industry to discuss and consider the critical sociological questions with which the research continues to grapple, and the cutting-edge methods and new types of data (or big data) with which actionable social knowledge can be elicited.
Cluster leader
Associate Professor, School of Journalism and Communication, CUHK
Research Interests
Computational Social Science, Social Media Analytics, Political Communicaion, Public Health
Affiliated members
Associate Professor
Research Interests
Medical Sociology, Social Epidemiology, Health Services Research, Demography, Sociology of Professions, Quantitative Methods
Assistant Professor
Research Interests
Social Networks, Computational Social Science
Associate Professor, Department of Educational Administration and Policy, CUHK
Research Interests
Economics of Education, Education Policy
Assistant Professor
Research Interests
Social Stratification, Education, Health, Children and Youth, Contemporary China, Quantitative Methods
Chair and Research Professor
Research Interests
Social Inequality, Sociology of Education, Economic Sociology
Assistant Professor
Research Interests
Organizational structure of political institutions and its influence on socio-economic development
Social stratification, income inequality and intergenerational mobility in China and US