Speaker: James Gleeson (Professor of Industrial and Applied Mathematics, MACSI, University of Limerick, Ireland)
Title:  Branching-process models for information spread

Date: Monday, April 28^th , 2025
Time: 11:00am-12:00pm
Location: Seminar room EXP-310
(Remote meeting is available: Zoom link.)

Abstract:  I will review some mathematical models of the spreading of information, with the goal of describing certain observed dynamics of posting on online boards such as Reddit. Time is (mostly) considered as continuous, so self-exciting point processes such as the Hawkes process are relevant. We examine the classical branching process interpretation of the Hawkes process and then seek generalizations to model the diurnal variation in activity that is characteristic of online social media. Using a large dataset of over 10^8 posts from online opinion boards, we demonstrate the possible utility of a very simple model that provides an explanation (of sorts) for how the time of day at which content is posted can affect its eventual popularity, as quantified by the number of comments it attracts. This is joint work with Joseph O’Brien, Alberto Aleta and Yamir Moreno.

Biography:   Professor James Gleeson holds the Chair in Industrial and Applied Mathematics at the University of Limerick. He is a graduate of University College Dublin in Mathematical Sciences and Mathematical Physics and received his PhD in Applied Mathematics from Caltech in 1999. Following his graduation from Caltech, he was a visiting assistant professor in Arizona State University, and then moved to University College Cork for 7 years, before taking up his current position at the University of Limerick. He is an Associate Editor of the Journal of Complex Networks and a member of the editorial board of Physical Review E. He is the director of the SFI Centre for Research Training in Foundations of Data Science (www.data-science.ie), which will produce 130+ PhD graduates with industry-ready skills. As co-director of MACSI, the Mathematics Applications Consortium for Science and Industry, he leads research into applications of mathematics to real-world problems with significant economic and social impact. His research interests include stochastic dynamics and contagion on complex networks.