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People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category
With this article, we present a repository containing datasets, analysis code, and some outputs related to a paper in press at Cognition. The data were collected as part of a pre-test, pilot test, and main study all designed in SurveyGizmo and participants recruited via Prolific.co (combined N=303)....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436764/ https://www.ncbi.nlm.nih.gov/pubmed/36060819 http://dx.doi.org/10.1016/j.dib.2022.108545 |
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author | Quinn, Molly S. Ford, Courtney Keane, Mark T. |
author_facet | Quinn, Molly S. Ford, Courtney Keane, Mark T. |
author_sort | Quinn, Molly S. |
collection | PubMed |
description | With this article, we present a repository containing datasets, analysis code, and some outputs related to a paper in press at Cognition. The data were collected as part of a pre-test, pilot test, and main study all designed in SurveyGizmo and participants recruited via Prolific.co (combined N=303). Datasets consist of raw and annotated data, where participant responses are free-text entries about what unexpected events might occur after a series of events, presented them with based on everyday scenarios. The code consists of all computational additions to the data, and analysis carried out for the results presented in the article. This data is released for the purpose of transparency and to allow for reproducability of the work. This human-labelled data should also be of use to machine learning researchers researching text analytics, natural language processing and sources of common-sense knowledge. |
format | Online Article Text |
id | pubmed-9436764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94367642022-09-03 People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category Quinn, Molly S. Ford, Courtney Keane, Mark T. Data Brief Data Article With this article, we present a repository containing datasets, analysis code, and some outputs related to a paper in press at Cognition. The data were collected as part of a pre-test, pilot test, and main study all designed in SurveyGizmo and participants recruited via Prolific.co (combined N=303). Datasets consist of raw and annotated data, where participant responses are free-text entries about what unexpected events might occur after a series of events, presented them with based on everyday scenarios. The code consists of all computational additions to the data, and analysis carried out for the results presented in the article. This data is released for the purpose of transparency and to allow for reproducability of the work. This human-labelled data should also be of use to machine learning researchers researching text analytics, natural language processing and sources of common-sense knowledge. Elsevier 2022-08-17 /pmc/articles/PMC9436764/ /pubmed/36060819 http://dx.doi.org/10.1016/j.dib.2022.108545 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Quinn, Molly S. Ford, Courtney Keane, Mark T. People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title | People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title_full | People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title_fullStr | People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title_full_unstemmed | People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title_short | People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
title_sort | people's reports of unexpected events for everyday scenarios: over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436764/ https://www.ncbi.nlm.nih.gov/pubmed/36060819 http://dx.doi.org/10.1016/j.dib.2022.108545 |
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