Like most people, Theresa O’Brien loves a laugh.
But the curious University of Wollongong School of Mathematics and Statistics student has always wondered whether the rumours were true about comedy television shows planting people in the audience to laugh at every joke.
So with the backing of her supervisors, Associate Professor Mark Nelson and Dr Tristram Alexander, Ms O’Brien set about finding out if there was a connection between maths and the spread of laughter.
Supported by an Australian Mathematical Sciences Institute (AMSI) Vacation Research Scholarship (VRS), Miss O’Brien is building a computer simulation of a comedy audience that represents people as programs called agents.
To do this Ms O’Brien collected recordings of stand-up comedy and used the volume of laughter as a way of estimating how much of the audience was laughing.
She will compare the proportion of the simulated audience against the real-world data to see if the model is realistic.
“This research helps us to understand contagious social behaviour. Laughter is one type, but there are others like information and opinion spread in social networks and this research may have extensions to those,” she said.
Ms O’Brien and other VRS program recipients were in Melbourne in February to present their research at the AMSIConnect Conference.
She was one of 69 mathematics and statistics students from 20 Australian universities who spent six weeks learning how to make high-impact mathematical discovery alongside some of Australia’s leading researchers.
AMSI director, Professor Tim Brown said the VRS program was fast becoming a must for students to build skills and knowledge through practical research application in a real-life setting.
Ms O’Brien agreed.
“The VRS experience has been a fantastic space for me to use my broad interdisciplinary background in social science as well as maths and stats,” she said.
“I have gained a lot of insight into how hard it is to model social behaviour with maths, because humans don’t lend themselves to this kind of research very well.
“We have to be really careful to not overstate our results and to verify our models because it’s much easier to program something completely unrealistic and disconnected from reality than something that reflects what people actually do.”
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