A hybrid system using PSO and data mining for determining the ranking of a new participant in Eurovision

The intention of the present work is to apply data mining and PSO to propose the solution of a specific problem about society modelling. We analyze the voting behavior and ratings of judges in a popular song contest held every year in Europe. The dataset makes it possible to analyze the determinants of success, and gives a rare opportunity to run a direct test of vote trading from logrolling. We show that they are rather driven by linguistic and cultural proximities between singers and voting countries. With this information it is possible to predict the final rank of a new country in the contest.