Temporal networks of human interaction
Abstract :
The power of any network approach lies in its ability to simplify a complex system so that one can better understand its function as a whole. However, sometimes it is beneficial to include more information than a simple graph of nodes and links alone. Adding information about interaction times can improve the accuracy of predictions and mechanistic understanding. The drawback, however, is that there are not many methods available, partly because the study of temporal networks is a relatively young field and partly because it is more difficult to develop such methods than for static networks. In this lecture, I will review methods for analyzing and modeling temporal networks and the processes that occur on them. Applications include the spreading of infectious diseases, opinions, and rumors in social networks; different types of search processes, delay propagation in traffic systems, data packet dynamics in computer networks; various types of signaling in biology, and more. We also discuss future
directions.
Biodata:
Petter Holme is a research leader (professor of network science at Aalto University, Computer Science) interested in interdisciplinary, often network-based, approaches to understanding society. Since his Ph.D. in theoretical physics, he has worked in Asia, America, and Europe, together with sociologists, economists, psychologists, demographers, chemists, engineers, biologists, ecologists, climate scientists, medical scientists, and more. Sometimes his research is more theoretical, and sometimes more applied. It could be mathematical, computational, data-driven, or experimental, but always guided by an overall ambition of understanding our world to make it better.