Project 4: Risk prevention
Together with our partners, such as Interpolis, we use data technologies to investigate how people cluster together in terms of their risk perception. The questions at the heart of this project are: How can we identify groups of people with similar risk perception and how can we reduce risky behavior by targeted communication with these groups? We investigate this based on anonymized data collected by our partners.
Data technologies for predicting behavior
Partners
The project
In data science, combining diverse data sources is key for revealing trends, improving predictions, and transforming information into usable knowledge. A cooperation between business, local government, and educational institutions offers an ideal structure to do so.
The aim of this project is to investigate if people's prevention behavior can be influenced more effectively by making communication more personal. Together with our partners, we develop models that give us insights in how people cluster together in terms of specific characteristics, such as their risk perception. This, in turn, allows partners to effectively communicate with various groups of people and inform them of possible undesirable consequences associated with their actions.
Some of the achievements in this project include creating interpretable predictive models. Additionally, we've played an active role in incorporating latest tools and techniques to facilitate data curation and analysis. This contributes to the improvement of the research in an efficient and effective way.
