Data in Brief (Oct 2022)

People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category

  • Molly S. Quinn,
  • Courtney Ford,
  • Mark T. Keane

Journal volume & issue
Vol. 44
p. 108545

Abstract

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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.

Keywords