Item Response Warehouse / Tables / sun_2026_tiktok_travelsun_2026_tiktok_travel
11,774 responses from 406 respondents to 29 items.
About this table
Description 29-item survey (7-point Likert) on information/service quality, destination image, emotion, and travel intention re: government-run tourism TikTok accounts, n=406 Reference Sun Y, et al (2026). Understanding travel intention formation in government culture and tourism TikTok accounts: An integration of the SOR model and emotion appraisal theory. PLOS ONE. DOI 10.1371/journal.pone.0349305 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0349305
Size and shape
Responses 11,774 Respondents 406 Items 29 Response categories 7 Responses per respondent 29 Responses per item 406 Density 1 Longitudinal FALSE
Classification
sample Internet-based measurement tool Survey/questionnaire item format Likert Scale/selected response primary language(s) chi
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
Instrument Questionnaire on the Influence of Government culture and tourism TikTok accounts on audience travel intentions Mean words per item 3.414 Mean characters per item 24.655 Mean characters per response 11.714 Flesch-Kincaid grade level 10.057
Columns
cov_birth_cohort cov_education cov_followed_account cov_gender cov_income cov_occupation cov_tiktok_use_duration id item resp
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sun_2026_tiktok_travel")
# Python
pip install irw
import irw
df = irw.fetch("sun_2026_tiktok_travel")
Version and provenance
IRW version v393 Redivis dataset item_response_warehouse_4 v7.0 Redivis dataset DOI 10.57761/cpj5-vm97 Manifest pin for this IRW version v7.0 Metadata source irw_meta v23.0
Part of the Item Response Warehouse , IRW v393. This page describes the table as released in item_response_warehouse_4 v7.0.