Erasmus University Rotterdam (EUR)
Browse
.DTA
ESC_individual_2014-2019.dta (5.47 MB)
TEXT
Do_analysis_ESC.do (5.36 kB)
1/0
2 files

Data: Disentangling Individual Biases in Jury Voting

dataset
posted on 2023-02-09, 08:28 authored by Oliver Budzinski, Sophia GaenssleSophia Gaenssle, Daniel Weimar

Dataset and code for in-depth analysis of ESC jury members and their voting behavior:


The Eurovision Song Contest is one of the worldwide biggest live media events and the world’s leading broadcast of an international music competition. A substantial list of cultural economics papers empirically analyzed the voting behavior of juries (consisting of music industry professionals) and audiences to identify voting biases because of cultural and political influences on the voting bodies. Due to limited data availability, this literature suffered from having to treat the national juries as a black box even though they are composed of individuals with different demographic characteristics (age, gender, etc.) and expert backgrounds (industry managers, musicians, composers, music journalists, etc.). Our analysis benefits from utilizing new data about each individual member of the jury including their role within the jury (e.g., the chairperson) as well as about their individual votes in the ESC. Therefore, for the first time, we can disentangle the voting behavior of the juries and track the voting behavior of individual jury members. 

History

Usage metrics

    Erasmus School of History, Culture and Communication

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC