From population pandemics to personal networking

How can an idea spreading on social networks and a disease infecting a population have anything in common?

Professor James Gleeson at University of Limerick has devised a mathematical model that can study both.

Prof Gleeson, Limerick’s co-director of the Mathematics Applications Consortium for Science and Industry (MACSI), says one of the challenges is analysing the probability of how a contagion might transfer from one object to another.

While there are mathematical models that can accurately predict how a disease will spread amongst individuals in a society, it is difficult due to the complexities of having so many entities in a large system. And being able to do this comes at a large computational cost. These models use people or whole cities as nodes, and it is how these nodes interact with their neighbours that will govern how a disease will progress.

Prof Gleeson has come up with a simpler approach that allows for faster analysis of how a disease spreads. Yet his new model is very general so the maths can be applied in many different ways, for example how people influence one another on social media.

The spread of a disease and the spread of an idea can be very similar, says Prof Gleeson. Researchers are currently trying to understand these interactions, and are doing so by using individuals as the model nodes. On social networking sites such as Facebook, for example, people are regarded as nodes, and how they interact with those in their friend lists can be used to track how an idea, or rumour, or an opinion can spread.

Prof Gleeson says that there is an opportunity here. With so much data piling up, and without the time to analyse it all, building these mathematical models has become a necessity. He believes because of this, it will be “one of the major new areas of research and innovation in the next few years”.

MACSI is a network of mathematicians and analysts that are funded by Science Foundation Ireland. They collaborate on mathematical research that can be used in real world applications.