Computational Social Science
Online debates, polarization and echo chambers, polluted information environments and online well-being, studied through large-scale social data.
Network Science
Dynamic, higher-order and feature-rich network models; community discovery, diffusion and opinion dynamics on and of complex networks.
Generative AI
How large language models reason, agree and persuade: cognitive biases, opinion dynamics among LLM agents and the interplay between human and machine cognition.
Social Twins
LLM-powered digital twins of social media platforms to run controlled, reproducible experiments on recommender systems, moderation and information spread.
What the SNA@KDD team works on
Each line collects its key questions, objectives and related publications.
Network Modeling
Dynamic, multilayer, higher-order and feature-rich network models, with algorithms and statistical validation for networked data.
Network Dynamics
Temporal network mining, dynamic community discovery and diffusion processes such as epidemics and opinion dynamics.
Online Debates
Polarization, echo chambers and polluted information environments: measuring, modelling and mitigating the pollution of online debates.
Online Well-Being
Supportive information environments and online self-help communities: their dynamics and their effect on well-being.
Cognitive NetSci
Feature-rich network models of the mental lexicon, language acquisition and emotional profiling of text.
LLM-based Opinion Dynamics
How populations of LLM agents form, exchange and change opinions when they debate in a network, and how they influence humans.