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UID:pretalx-europython-2026-UPELCT@programme.europython.eu
DTSTART;TZID=CET:20260715T122000
DTEND;TZID=CET:20260715T125000
DESCRIPTION:<b>Graphs</b> offer a powerful tool for uncovering relationship
 s and hidden patterns between entities. This presentation provides an intr
 oduction to <b>graph theory</b>\, and demonstrates how graphs are applied 
 across various business domains - from social network analysis and recomme
 ndation systems to fraud detection and supply chain optimization. Through 
 an overview of core concepts and algorithmic approaches\, the goal is to s
 how how graphs can reveal underlying structures in complex systems.\n\nAs 
 a real-world case study\, the presentation focuses on <b>Eurovision voting
 </b> - an area long suspected of regional bias and neighbourly favoritism.
  Using graph-based analysis and community detection techniques\, we explor
 e voting patterns between countries to better understand how geography\, h
 istory\, and politics influence the distribution of points. Through visual
 izations and data-driven insights\, the talk demonstrates how graph theory
  uncovers hidden alliances and behavioral trends within the seemingly ligh
 t-hearted spectacle of a music contest.
DTSTAMP:20260524T130631Z
LOCATION:Conference Hall Complex (S4)
SUMMARY:Friendly Borders: Graph algorithms reveal Eurovision voting pattern
 s - Domagoj Marić
URL:https://programme.europython.eu/europython-2026/talk/UPELCT/
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