A Hybrid System Approach to Determine the Ranking of a Debutant Country in Eurovision

The goal of the present work is to apply the computational properties of cultural technology, such as data mining and, to propose the solution of a real problem about society modeling: the Eurovision Song Contest. We analyze the voting behavior and ratings of judges using data mining techniques. 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 rank of a new country, distributing a number of votes of all the participants. A computer model is proposed and solved using a technique based on Particle Swarm Optimization.