The Research lab of Dr. Niko Yiannakoulias
The Socio-Environmental Systems Lab is an interdisciplinary research laboratory that studies complex socio-environmental systems. Our objective is to understand how our collective and individual decisions influence the use and operation of social and environmental systems. Our research covers a number of topics areas, including risk analysis, health and disease, environmental change, information science and risk communication. We use methods in experimental social science, game theory, machine learning and geographic information science.
The Socio-Environmental Systems Lab is in the School of Earth, Environment and Society at McMaster University.
If you are a prospective grad student, please click here to learn about opportunities in the lab.
Check out https://www.decisiongame.ca to see some active research experiments and education games.
We developed a game for exploring pedestrian and cycling safety preferences, and then used that information to paramaterize an agent based model. This model was then used to explore the impact of safety infrastructure change.
In this project we evaluated methods for estimating residential building populations using building footprint, volume and some modelling.
Here I describe a gaming approach to learning about cap and trade markets. Future research will collect information from players to measure the efficacy of games in learning.
This study found that some high flood hazard areas in the City of Calgary are in areas with lower levels of social vulnerability, and that dwelling value has increased faster in high flood hazard areas than low flood hazard areas.
This study was a critical investigation of quality of publicly available Covid-19 data during the first 8 months of the pandemic. Our analysis revealed that most data had little to no information value over the short term, and that these data may not be informing us about anything that helps manage individual or social risks of disease.
In this research we analyzed anti- and pro- immunization content on YouTube and found evidence that anti-immunization content might be easy to identify using natural language processing (NLP). We also found that pro-immunization content is may be more effectively communicated when infection risk is on the rise.
This research describe a method for collecting data on risk management decisions using an online decision game. We found that people who played the game adopted a role playing behaviour that suggests games can be useful for understanding risk management decisions.
In this study we analyzed Tweets from public health accounts in Canada during the first 6 months of the Covid-19 pandemic. Our results highlighted the need for public health to deliver messages consistent with local levels of risk.