Many problems involve not structured environments which can be solved from the perspective of particle swarm optimization (PSO). In this research analyze the voting behavior 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 score of a new country, redistributed the assigned votes for a lot of the participants, this paper tries to explain this social behavior.