It has been the historic responsibility of the social sciences to investigate human societies.
Fulfilling this responsibility requires social theories, measurement models and social data …

Graph neural networks (GNNs) have emerged as a powerful tool for effectively mining and
learning from graph-structured data, with applications spanning numerous domains …

Societal transformations are necessary to address critical global challenges, such as
mitigation of anthropogenic climate change and reaching UN sustainable development …

Despite the prevalence of recent success in learning from static graphs, learning from time-
evolving graphs remains an open challenge. In this work, we design new, more stringent …

Human social interactions in local settings can be experimentally detected by recording the
physical proximity and orientation of people. Such interactions, approximating face-to-face …

Complex systems must respond to external perturbations and, at the same time, internally
distribute information to coordinate their components. Although networked backbones help …

Non-pharmaceutical interventions are crucial to mitigate the COVID-19 pandemic and
contain re-emergence phenomena. Targeted measures such as case isolation and contact …

Effective control of an epidemic relies on the rapid discovery and isolation of infected
individuals. Because many infectious diseases spread through interaction, contact tracing is …

Recent studies have shown that novel collective behaviors emerge in complex systems due
to the presence of higher-order interactions. However, how the collective behavior of a …

Digital contact tracing is a relevant tool to control infectious disease outbreaks, including the
COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features …