@inproceedings{beckles-etal-2025-cowoytp1att,
title = "{C}o{W}o{YTP}1{A}tt: A Social Media Comment Dataset on Gender Discourse with Appraisal Theory Annotations",
author = "Beckles, Valentina Tretti and
Heidke, Adrian Vergara and
Molina-Valverde, Natalia",
editor = "Alam, Mehwish and
Tchechmedjiev, Andon and
Gracia, Jorge and
Gromann, Dagmar and
di Buono, Maria Pia and
Monti, Johanna and
Ionov, Maxim",
booktitle = "Proceedings of the 5th Conference on Language, Data and Knowledge",
month = sep,
year = "2025",
address = "Naples, Italy",
publisher = "Unior Press",
url = "https://aclanthology.org/2025.ldk-1.4/",
pages = "31--42",
ISBN = "978-88-6719-333-2",
abstract = "This paper presents the Corpus on Women in YouTube on Performance with Attitude Annotations (CoWoYTP1Att), developed based on Appraisal Theory (Martin {\&} White, 2005). Between September 2020 and May 2021, 14,883 comments were extracted from a YouTube video featuring a compilation of the performance ``Un violador en tu camino'' (A Rapist in Your Path) by the feminist collective LasTesis, published on the channel of the Costa Rican newspaper La Naci{\'o}n. The extracted comments were manually and automatically classified based on several criteria to determine their relevance to the video. As a result, 5,939 comments were identified as related to the video. These comments were annotated with the three attitude subdomains (affect, judgement, and appreciation) proposed on the Appraisal Theory (Martin {\&} White, 2005), as well as their polarity, target, fragment, and whether the attitude was implicit or explicit. The statistical analysis of the corpus highlights the predominant negative evaluation of individuals present in the comments on this social media platform."
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%0 Conference Proceedings
%T CoWoYTP1Att: A Social Media Comment Dataset on Gender Discourse with Appraisal Theory Annotations
%A Beckles, Valentina Tretti
%A Heidke, Adrian Vergara
%A Molina-Valverde, Natalia
%Y Alam, Mehwish
%Y Tchechmedjiev, Andon
%Y Gracia, Jorge
%Y Gromann, Dagmar
%Y di Buono, Maria Pia
%Y Monti, Johanna
%Y Ionov, Maxim
%S Proceedings of the 5th Conference on Language, Data and Knowledge
%D 2025
%8 September
%I Unior Press
%C Naples, Italy
%@ 978-88-6719-333-2
%F beckles-etal-2025-cowoytp1att
%X This paper presents the Corpus on Women in YouTube on Performance with Attitude Annotations (CoWoYTP1Att), developed based on Appraisal Theory (Martin & White, 2005). Between September 2020 and May 2021, 14,883 comments were extracted from a YouTube video featuring a compilation of the performance “Un violador en tu camino” (A Rapist in Your Path) by the feminist collective LasTesis, published on the channel of the Costa Rican newspaper La Nación. The extracted comments were manually and automatically classified based on several criteria to determine their relevance to the video. As a result, 5,939 comments were identified as related to the video. These comments were annotated with the three attitude subdomains (affect, judgement, and appreciation) proposed on the Appraisal Theory (Martin & White, 2005), as well as their polarity, target, fragment, and whether the attitude was implicit or explicit. The statistical analysis of the corpus highlights the predominant negative evaluation of individuals present in the comments on this social media platform.
%U https://aclanthology.org/2025.ldk-1.4/
%P 31-42
Markdown (Informal)
[CoWoYTP1Att: A Social Media Comment Dataset on Gender Discourse with Appraisal Theory Annotations](https://aclanthology.org/2025.ldk-1.4/) (Beckles et al., LDK 2025)
ACL