mercea_2025_movement_parties

103,470 rated or chosen profiles from 10,347 respondents, in up to 5 tasks of 2 profiles varying on 5 attributes.

About this table

DescriptionYouGov respondents in Denmark, Germany, Hungary, Italy, Romania and the UK (Feb-Mar 2022; n=10,347) each made 5 forced choices between two hypothetical parliamentary candidates varying in institutional and extra-institutional experience, reason for running, and migration and climate positions, and rated each candidate 1-7.
ReferenceMercea, D., & Santos, F. G. (2025). Policy over protest: Experimental evidence on the drivers of support for movement parties. Perspectives on Politics, 23(3), 901-923.
DOI10.1017/S1537592724001439
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/CBKZL1

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents10,347
Rows (one per respondent, task and profile)103,470
Tasks per respondent (most)5
Profiles per task2
Attributes5
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryDK, DE, HU, IT, RO, GB
Language shownda, de, hu, it, ro, en
Language of stored levelsen
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceIf you had to choose between them, which candidate do you prefer? [choice, forced]
ratingHow much do you approve or disapprove of this candidate? (paraphrase) [rating, 1 (Strongly disapprove) to 7 (Strongly approve)]

Columns

attr_environment_positionattr_extrainstitutional_experienceattr_institutional_experienceattr_migration_positionattr_reason_for_runningchoicecov_countrycov_past_votecov_survey_weightidprofileratingtask

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

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("mercea_2025_movement_parties", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("mercea_2025_movement_parties", source="conj")

How to cite

@article{Mercea_2024, title={Policy over Protest: Experimental Evidence on the Drivers of Support for Movement Parties}, volume={23}, ISSN={1541-0986}, url={http://dx.doi.org/10.1017/S1537592724001439}, DOI={10.1017/s1537592724001439}, number={3}, journal={Perspectives on Politics}, publisher={Cambridge University Press (CUP)}, author={Mercea, Dan and Santos, Felipe G.}, year={2024}, month=Nov, pages={901–923} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0