Over the past decade, computational social science (CSS) has risen as an interdisciplinary field that combines methods and theories from computer science, statistics, and social sciences to study complex social phenomena using computational tools and techniques. 

By leveraging the power of computing and data, computational social scientists aim to uncover patterns and trends in complex social systems that may be difficult or impossible to discern through traditional research methods. 

Topics of interest include social networks, online communities, opinion dynamics, and collective decision-making, among others. Computational social science has become increasingly important as our world becomes more digitised, and its insights have significant implications for fields such as public policy, marketing, and sociology.

The First edition of the school Computational Social Science: Advances, Challenges and Opportunities is designed to provide an intensive and immersive learning experience for graduate students, postdoctoral researchers, and early career faculty interested in utilising computational methods to study social phenomena.