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). 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.

Abstract licence: CC BY-NC

2 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.