A study on the impact of crowd-based voting schemes in the 'Eurovision' European contest
EntityUAM. Departamento de Ingeniería Informática
10.1145/1988688.1988718WIMS '11: Proceedings of the International Conference on Web Intelligence, Mining and Semantics, ACM, 2011. 25
Funded byThis work has been funded by the Spanish Ministry of Science and Technology under the projects ABANT (TIN2010 19872)
SubjectsCPM; Data mining; Edge betweenness; Eurovision; Graph based algorithms; Network; Social mining; Televoting; Voting partnership; Web mining; Informática
NoteThis is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in WIMS '11 Proceedings of the International Conference on Web Intelligence, Mining and Semantics, http://dx.doi.org/10.1145/1988688.1988718.
Rights© 2011 ACM
The Eurovision contest has been the reference on european song contests for the past 50 years. Countries in the European Union can shows the rest of the participants their current music tendencies. This phenomena has been studied in domains like physic and social sciences to find correlations between contests and current political and socio-economy trends in EU. The inclusion of web and social technologies some years ago, have caused a disruption in the traditional voting system whereby the audience is encouraged to participate by casting votes for their favorite song. As a result, this system yields new, relevant information that may be extrapolated to social and political tendencies in Europe with a higher degree accuracy than by data collected using the previous jury-based system. This paper provides an initial data analysis in crowd behavior to assess the impact of the televote system, in the Eurovision voting dynamic, by focusing on two distinct five years periods that can successfully contrast each voting scheme. Analyzing these periods separately, we can observe results from the televoting contests and then compare to the jury to see if there is a change in voting patterns. Finally, we study the underlying community structure of the voting network using the Cluster Percolation Method and Edge Betweenness to discover stable core communities spanning a number of years in the contest. The clusters obtained using these algorithms are then used to compare how these stable communities have evolving during the considered periods.
This item appears in the following Collection(s)
Showing items related by title, author, creator and subject.
Bello-Orgaz, Gema; Hernandez-Castro, Julio; Camacho, David