The complexity of human proximity networks

Keynote presentation by Ciro Cattuto, ISI Foundation

Digital technologies allow us to quantify many important human behaviors and have revolutionised how we think about human mobility, opening new avenues for research in computational social science, urban mobility, computational epidemiology, and public health. This talk will focus on human proximity networks measured using wearable proximity sensors. We will discuss the evolution and state of the art of measurement technology and the lessons learned from data collection experiences in various real-world environments, including schools, hospitals, households, low-resource rural settings, and more. We will illustrate the complex features and emergent patterns of time-resolved proximity networks and discuss how ideas and methods from network science and machine learning can support their modeling in important application scenarios. We will close by discussing the privacy implications of collecting fine-grained behavioral data and focus, in particular, on the experience of smartphone apps for COVID-19 digital contact tracing.