torok_2025_discourse_responsibility

5,441 responses from 940 respondents to 6 items.

About this table

DescriptionHow far each of 6 named actors should be responsible for improving the quality of online discourse, 1-5 scale, a nationally representative CATI sample of Hungarian adults, fielded 2019. 5,441 responses from 940 respondents on 6 items.
ReferenceTorok, B., Rab, A., Punkosty, A., Labody, P., Sorban, K., Menyhard, A., Szikora, T., Vadasz, P., & Zodi, Z. (2025). Trust, Awareness, and Risk Perception in the Online Environment [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15168213
LicenceCC BY 4.0
Source datahttps://zenodo.org/records/15168213

Size and shape

Responses5,441
Respondents940
Items6
Response categories5
Responses per respondent5.788
Responses per item906.833
Density0.965
LongitudinalFALSE

Classification

age rangeAdult (18+)
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)hun

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentÖn szerint mennyire lenne feladatuk javítani a párbeszéd színvonalán a következő szereplőknek?
Mean words per item2.500
Mean characters per item29.833
Mean characters per response15.200
Flesch-Kincaid grade level12.918

Columns

cov_agecov_children_under14cov_countycov_educationcov_gendercov_household_sizecov_regioncov_settlement_typeiditemresp

Get the data

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

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("torok_2025_discourse_responsibility")
# Python
pip install irw

import irw
df = irw.fetch("torok_2025_discourse_responsibility")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_5 v4.0
Redivis dataset DOI10.57761/yvjw-0981
Manifest pin for this IRW versionv4.0
Metadata sourceirw_meta v23.0