Computational Social Dynamics is dedicated to using computational methods, artificial intelligence, data science, and complex systems theory to study the formation mechanisms, evolutionary processes, and interactions of social, economic, organizational, and cultural phenomena. It focuses on the dynamic relationships among individual behavior, group interaction, social networks, and technological systems. The journal integrates computational social science, computer science, artificial intelligence, network science, economics, behavioral science, digital humanities, and complex systems research, and encourages computational modeling, machine learning, simulation analysis, and data-driven methods to deepen understanding of complex social phenomena.

The journal addresses frontier areas such as generative artificial intelligence and multi-agent systems, social networks and collective behavior, algorithmic governance, computational economics, and AI-assisted scientific discovery. It welcomes research with clear methodological innovation, theoretical value, or practical significance. The journal emphasizes reproducibility, model validation, data quality, algorithmic transparency, and the social implications of technological applications, aiming to promote deep integration between intelligent computing technologies and social science questions.