Overview

DySoC unites members, students, and international collaborators under three primary research themes:

Computational Social Science: This theme focuses on identifying coherent patterns in complex, large-scale human behavioral data. In highly interconnected domains such as public health, socio-economic change, and environmental challenges, computational approaches provide crucial insights. These societal challenges are rapidly evolving, characterized by ephemeral, indirect, conflicting, and interdependent evidence. DySoC’s research in this area aims to develop tools and frameworks to better understand and respond to these dynamic changes.

Cultural Evolution: This field examines the co-evolution of human cognition, culture, and societies. It seeks to uncover fundamental mechanisms of cooperation and conflict across time, from ancient civilizations to contemporary societies, and even the emerging influence of new technologies and media. DySoC’s research delves into these processes to gain a deeper understanding of social change across different eras.

The Social Complexity of Science: This theme explores how scientific innovation emerges within an ever-growing body of knowledge, extending into broader social networks and cultures. DySoC investigates how scientific knowledge flows across nations and institutions and how misinformation, particularly driven by AI, affects public trust in science, civic values, and global narratives.