Friendly Borders: Graph algorithms reveal Eurovision voting patterns
Conference (INTERMEDIATE level)
Room C
Graphs offer a powerful tool for uncovering relationships and hidden patterns between entities. This presentation provides an introduction to graph theory, and demonstrates how graphs are applied across various business domains - from social network analysis and recommendation systems to fraud detection and supply chain optimization. Through an overview of core concepts and algorithmic approaches, the goal is to show how graphs can reveal underlying structures in complex systems.
As a real-world case study, the presentation focuses on Eurovision voting - an area long suspected of regional bias and neighbourly favoritism. Using graph-based analysis and community detection techniques, we explore voting patterns between countries to better understand how geography, history, and politics influence the distribution of points. Through visualizations and data-driven insights, the talk demonstrates how graph theory uncovers hidden alliances and behavioral trends within the seemingly light-hearted spectacle of a music contest.
As a real-world case study, the presentation focuses on Eurovision voting - an area long suspected of regional bias and neighbourly favoritism. Using graph-based analysis and community detection techniques, we explore voting patterns between countries to better understand how geography, history, and politics influence the distribution of points. Through visualizations and data-driven insights, the talk demonstrates how graph theory uncovers hidden alliances and behavioral trends within the seemingly light-hearted spectacle of a music contest.
Domagoj Marić
Pontis Technology
Domagoj Marić graduated from the Faculty of Electrical Engineering and Computing in Zagreb, shifting from information security to data science with a focus on web scraping. He began his career at Megatrend poslovna rješenja developing Python applications and data solutions, later leading the data science department, a role he continued at Comping. Today, he works as the AI Customer Delivery Manager at Pontis Technology, leading the delivery of projects in NLP, computer vision, predictive analytics, and generative AI. In addition to his industry work, he also works as a lecturer in programming.