emobank_buechel_2017

318,519 responses from 10,548 respondents to 6 items.

About this table

DescriptionEmoBank, a large-scale text corpus manually annotated with emotion according to the psychological Valence-Arousal-Dominance scheme
ReferenceSven Buechel and Udo Hahn. 2017. EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 578–585, Valencia, Spain. Association for Computational Linguistics.
DOIhttps://zenodo.org/records/7440748
LicenceCC BY-SA 4.0
Source datahttps://github.com/JULIELab/EmoBank

Size and shape

Responses318,519
Respondents10,548
Items6
Response categories5
Responses per respondent30.197
Responses per item53086.500
Density5.033
LongitudinalFALSE

Classification

age rangeNon-human
sampleTargeted/specific
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameEmobank

Item text

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

InstrumentEmoBank crowdsourced VAD annotation task (5-point Self-Assessment Manikin: Pleasure, Arousal, Control)
Mean words per item115
Mean characters per item773.833
Mean characters per response12.867
Flesch-Kincaid grade level9.787

Columns

iditemresp

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("emobank_buechel_2017")
# Python
pip install irw

import irw
df = irw.fetch("emobank_buechel_2017")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0