Welcome to CanPol Tracker
Election Coverage Decoded with Artificial Intelligence
CanPol Tracker is a cutting-edge platform that leverages artificial intelligence (AI), big data techniques, and large language models (LLMs) to reveal how Canadian English news outlets portray major political parties and key election issues.
Trained on a vast and continuously expanding dataset of national and local news sources, these models are capable of decoding complex language and capturing the underlying tone and focus of media coverage.
What We Offer
Media Coverage by Party
See how much attention each party receives, and from which outlets.
Key Issues by Party and Outlet
Discover the main topics shaping the campaign and how they vary by media source.
Sentiment Trends
Track the tone of coverage (positive, negative, neutral) by issue, party, and outlet.
Powered by cutting-edge LLMs
Our models decode nuanced and complex language across thousands of articles weekly.
About CanPol Tracker
Our current tracker covers the 100 days before the campaign and the entire campaign period, with weekly updates. Our broader dataset spans over five decades of Canadian political news, offering a unique historical perspective and deep analytical capacity.
CanPol Tracker can help voters, researchers, journalists, firms, and policymakers better understand the evolving political landscape.
Note: Positive or negative sentiment in media coverage does not necessarily translate into electoral outcomes. While media tone may signal shifting narratives or public interest, it is not necessarily a predictor of voting behavior. Political dynamics remain complex and often unpredictable.
Disclaimer: CanPol Tracker is an independent tool. The views expressed do not reflect those of the authors' institutions or affiliations.
Meet Our Team
The experts behind CanPol Tracker bringing together expertise in political science, data analytics, and AI.
Firmin Ayivodji
Economist, International Monetary Fund (IMF)
Firmin Ayivodji is an economist at the International Monetary Fund (IMF), specializing in IMF program design, macro-financial modeling, and big data applications. He holds a PhD in Economics and Data Science from the University of Montreal (UdeM). His work focuses on econometrics, big data, machine learning, NLP, large language models (LLMs), generative AI, and climate finance, with applications in macro-finance, causal inference, and political science.
He has held positions at the Bank of Canada, the World Bank, and in the tech industry as an AI Scientist. He also advised the UNDP and the Government of Benin on the use of artificial intelligence and big data strategies for long-term national planning. Previously, he was a research economist at the Observatoire de la Francophonie Économique (OFE) and taught at the University of Montreal.
His work has been recognized by Stanford University as a 2024 Rising Star in Management Science & Engineering and by the Becker Friedman Institute as a Macro-Finance Research Young Scholar. In August 2024, he was a visiting scholar at the University of Chicago Booth School of Business.
Gedeon Gbedonou
Aspiring AI Engineer
Gedeon Gbedonou is an aspiring AI engineer and software developer working at the crossroads of artificial intelligence, economics, and climate change. As a research assistant under Firmin Ayivodji, he applies natural language processing and machine learning techniques—including sentiment analysis and GPT-based models—to explore macroeconomic perceptions, climate policy discourse, and public opinion.
He holds a Bachelor’s degree in Computer Science from the National School of Applied Economics and Management in Benin and has enhanced his training through programs like iSheero’s Africa TechUp Tour. His technical skills include Python, NLP, and web development. Gedeon has contributed to projects such as multilingual dubbing solutions for underrepresented Benin languages and LLM-powered chatbots for public health and events.
Gedeon also volunteers with Tekbot Robotics and iSheero, leading AI training and solution design. His innovative work earned him the 2024 Benin Multimodal AI Hackathon Award. Passionate about sustainable development, he aims to become a leading AI researcher focused on climate and economic solutions that advance equity in Africa and beyond.
Interested in collaborating or learning more about our research?
Get in Touch
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