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Eurovision Data Literacy Project

We analyzed Eurovision voting patterns to determine the effect of distance and took into account external factors such as GDP per capita and music similarity determined from Spotify data.

Methods

After collecting and cleaning it, we analyzed the data using :

  • Overall linear regression
  • a Linear Mixed Model
  • country-wise linear regression
  • K-means clustering and visualization using PCA

Project Members

  • Keyu Wang
  • Kai Lüdemann
  • Pablo Santos Blázquez
  • Valentin Schmidt

Legal Notice

This is a university project and may be copied without at least one authors explicit permission. The datasets may not be downloaded or copied. This especially includes the WRP Religion dataset (Zeev Maoz and Errol A. Henderson. 2013. “The World Religion Dataset, 1945-2010: Logic, Estimates, and Trends.” International Interactions, 39: 265-291.)

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Data literacy project for 2024 to analyze geopolitical patterns in Eurovision voting

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