Ludic tool serving political science research Université Laval




Cloud native development




Datagotchi is an educational and playful web application that engages the user in the interactive design of a personalized avatar. This new Datagotchi folder, 'Quebec Elections 2022,' aims to shed light on the relationship between voting intentions and lifestyle habits, thereby raising awareness among citizens about the richness and power of big data.

Datagotchi is an initiative led jointly by Simon Coulombe, Associate Professor in Industrial Relations at Laval University, Yannick Dufresne, Associate Professor in Political Science at Laval University and holder of the Chair of Leadership in Digital Social Sciences Education (CLESSN), and Catherine Ouellet, Ph.D. student in Political Science at the University of Toronto. The team behind Datagotchi has devoted considerable efforts to obtain the most rigorous ethical approvals, as expected of an application that collects individual data. Thus, it can guarantee its users the highest standards of privacy and data security.

L’équipe de Datagotchi s’engage à traiter les données des utilisateurs de manière confidentielle et sécurisée lorsqu’ils remplissent le questionnaire sur l’application. The questions about the sociodemographic characteristics of users, as well as their lifestyle habits, allow predicting the probability that the user will vote for each of the following five provincial parties: Coalition avenir Québec, Parti libéral du Québec, Québec solidaire, Parti québécois, and Parti conservateur du Québec. All parties for which the vote projections were 5% or more before the start of the campaign are considered in the analysis. We therefore exclude parties further on the margins such as: the Green Party of Quebec (PVQ), Mouvement Québec français (MQF), and the Parti canadien du Québec. For now, the percentage of voters supporting these parties is too low to fuel the prediction algorithm. However, the predictive model is continuously refined and adjusted based on respondents, so these parties could potentially be included in Datagotchi if they reach the threshold of voter intention in the Quebec electorate.

To access the full methodology (PDF), click here!

Inference of prediction


"We have a wealth of data and scientific knowledge but lack technical expertise, which is why we started working with Unicorne. "