From Social Network Analysis to Simulating Societies: Recent Research in Computational Social Science at KDD Lab

Computational social science is evolving beyond the analysis of social networks toward the development of computational models capable of reproducing and exploring the dynamics of entire societies. This talk presents recent research from the KDD Lab @ ISTI-CNR, outlining a common vision that bridges the study of online social systems with the emerging paradigm of AI-driven social simulation. The journey begins with network modeling and the analysis of online phenomena, including debate polarization and echo chambers, and the identification of supportive interactions and resilient communities. It then moves to the characterization of Large Language Models as computational models of social cognition, examining their biases, semantic organization through resources such as the LLM World of Words (LWOW) dataset, and their tendency to exploit logical fallacies when debating in multi agent systems. Finally, the talk explores LLM-based social simulations, where generative agents interact within synthetic social environments to investigate the emergence of collective behavior and assess interventions in silico. Together, these research directions illustrate how computational social science is progressing from understanding social networks to building computational models of digital societies.

Giulio Rossetti is a Senior Researcher at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), where he leads the Social Network Analysis unit of the KDD laboratory. His work lies at the crossroads of modeling and understanding complex social systems through network science, large-scale online data analysis, and generative AI. His recent research spans online polarization, opinion dynamics, supportive communities, “cognitive” biases of large language models, and IA-powered social simulations.