mummolo_2016_news_choice

25,416 rated or chosen profiles from 1,059 respondents, in up to 12 tasks of 2 profiles varying on 2 attributes.

One of 2 tables from the same source; this one is the choice table. The others are listed under Related tables.

About this table

DescriptionUS Democrats and Republicans from the main sample (provider not stated in the deposit) (n = 1,059) made 12 choices between two news items, each a headline (11 topics x 3 wordings) attributed to Fox News, MSNBC or USA Today.
ReferenceMummolo, J. (2016). News from the other side: How topic relevance limits the prevalence of partisan selective exposure. The Journal of Politics, 78(3), 763-773.
DOI10.1086/685584
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/HQKQCQ

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

Respondents1,059
Rows (one per respondent, task and profile)25,416
Tasks per respondent (most)12
Profiles per task2
Attributes2
Tasks with no profile chosen0

Design

Topicpolitical communication
A profile representsmessage
CountryUS
Language shownen
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceWhich of these two news stories would you choose to read? (paraphrase) [choice, forced]

Columns

attr_headlineattr_sourcechoicecov_agecov_bacov_blackcov_concov_demcov_gender_codecov_health_care_jobcov_incomecov_latinocov_libcov_lose_weightcov_other_racecov_repcov_seniorcov_smokercov_studentcov_uninsuredcov_whiteidprofiletasktrial_rowstrial_scheme

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("mummolo_2016_news_choice", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("mummolo_2016_news_choice", source="conj")

How to cite

@article{Mummolo_2016, title={News from the Other Side: How Topic Relevance Limits the Prevalence of Partisan Selective Exposure}, volume={78}, ISSN={1468-2508}, url={http://dx.doi.org/10.1086/685584}, DOI={10.1086/685584}, number={3}, journal={The Journal of Politics}, publisher={University of Chicago Press}, author={Mummolo, Jonathan}, year={2016}, month=July, pages={763–773} }

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