A Crowd-Annotated Spanish Corpus for Humor Analysis

Santiago Castro, Luis Chiruzzo, Aiala Rosá, Diego Garat, Guillermo Moncecchi


Abstract
Computational Humor involves several tasks, such as humor recognition, humor generation, and humor scoring, for which it is useful to have human-curated data. In this work we present a corpus of 27,000 tweets written in Spanish and crowd-annotated by their humor value and funniness score, with about four annotations per tweet, tagged by 1,300 people over the Internet. It is equally divided between tweets coming from humorous and non-humorous accounts. The inter-annotator agreement Krippendorff’s alpha value is 0.5710. The dataset is available for general usage and can serve as a basis for humor detection and as a first step to tackle subjectivity.
Anthology ID:
W18-3502
Volume:
Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Lun-Wei Ku, Cheng-Te Li
Venue:
SocialNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7–11
Language:
URL:
https://aclanthology.org/W18-3502
DOI:
10.18653/v1/W18-3502
Bibkey:
Cite (ACL):
Santiago Castro, Luis Chiruzzo, Aiala Rosá, Diego Garat, and Guillermo Moncecchi. 2018. A Crowd-Annotated Spanish Corpus for Humor Analysis. In Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media, pages 7–11, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
A Crowd-Annotated Spanish Corpus for Humor Analysis (Castro et al., SocialNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-3502.pdf
Presentation:
 W18-3502.Presentation.pdf