1,800 marked positions from 105 rankers over 18 options.
One of 15 tables from the same source; this one is the 2019_sf2 table. The others are listed under Related tables.
| Description | Eurovision Song Contest 2019 semi-final 2: each of the five anonymous jurors (A-E) in every national jury ranks all songs in the show except their own country's; 18 songs, 105 jurors with a ranking (of 105 juror slots across 21 juries). One row per juror x song; item = performing country's ISO code (songs are not people, so the label is kept), resp = rank given (1 = best); cov_jury_country = voting country, cov_juror = letter. Rankings layout (draft irw_rankings family, data/rankings/README.md). |
|---|---|
| Reference | Burgoyne, J. A., Spijkervet, J., & Baker, D. J. (2023). Measuring the Eurovision Song Contest: A living dataset for real-world MIR. Proceedings of ISMIR 2023. Data: https://doi.org/10.5281/zenodo.10265412 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.5281/zenodo.10265412 |
| Items | 18 |
|---|---|
| Rankers | 105 |
| Marked positions (one row each) | 1,800 |
| Rankings per respondent | 1 |
| Counting method | jury |
| Positions offered | 18 |
| Candidates | 18 |
| Ballots cast | 105 |
| Ballots with marks | 105 |
| Duplicate marks | 0 |
| Overvotes | 0 |
| Write-ins | 0 |
| Write-in allowed | no |
| Candidate order | fixed |
| Jurisdiction | Eurovision Song Contest |
| Contest date | unknown |
| Office | 2019 semi-final-2 jury ranking |
cov_jurorcov_jury_countryiditemresptask
The layout (one row per respondent, ranking and marked position; resp the position as recorded, 1 = first choice; item a candidate code c01, c02, … or a reserved value) is defined in the IRW rankings standard. Skipped positions are gaps and duplicate marks are kept, so compress with irw_rank_compress() / irw.rank_compress() before a person-by-item pivot.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("eurovision_2019_sf2", source = "rank")
# Python
pip install irw
import irw
df = irw.fetch("eurovision_2019_sf2", source="rank")
@article{https://doi.org/10.5281/zenodo.10265412,
doi = {10.5281/ZENODO.10265412},
url = {https://zenodo.org/doi/10.5281/zenodo.10265412},
author = {John Ashley Burgoyne, and Janne Spijkervet, and David John Baker, },
title = {Measuring the Eurovision Song Contest: A Living Dataset for Real-World MIR},
publisher = {ISMIR},
year = {2023},
copyright = {Creative Commons Attribution 4.0 International}
}
| IRW version | v581 |
|---|---|
| Redivis dataset | irw_rank v1.1 |
| Redivis dataset DOI | 10.57761/amk1-y692 |
| Manifest pin for this IRW version | v1.0 |
| Metadata source | irw_meta v44.0 |