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Humor appreciation can be predicted with machine learning techniques

Crossref DOI link: https://doi.org/10.1038/s41598-023-45935-1

Published Online: 2023-11-03

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Rosenbusch, Hannes https://orcid.org/0000-0002-4983-3615
Visser, Thomas
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Text and Data Mining valid from 2023-11-03

Version of Record valid from 2023-11-03
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Article History

Received: 21 June 2023

Accepted: 25 October 2023

First Online: 3 November 2023

Competing interests

: The authors declare no competing interests.