@inproceedings{ruiter-etal-2022-placing,
title = "Placing {M}-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online",
author = "Ruiter, Dana and
Reiners, Liane and
D{'}Sa, Ashwin Geet and
Kleinbauer, Thomas and
Fohr, Dominique and
Illina, Irina and
Klakow, Dietrich and
Schemer, Christian and
Monnier, Angeliki",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.84",
pages = "791--804",
abstract = "Even though hate speech (HS) online has been an important object of research in the last decade, most HS-related corpora over-simplify the phenomenon of hate by attempting to label user comments as {``}hate{''} or {``}neutral{''}. This ignores the complex and subjective nature of HS, which limits the real-life applicability of classifiers trained on these corpora. In this study, we present the M-Phasis corpus, a corpus of {\textasciitilde}9k German and French user comments collected from migration-related news articles. It goes beyond the {``}hate{''}-{``}neutral{''} dichotomy and is instead annotated with 23 features, which in combination become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of hate. The annotations are performed by 4 native speakers per language and achieve high (0.77 {\textless}= k {\textless}= 1) inter-annotator agreements. Besides describing the corpus creation and presenting insights from a content, error and domain analysis, we explore its data characteristics by training several classification baselines.",
}
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<abstract>Even though hate speech (HS) online has been an important object of research in the last decade, most HS-related corpora over-simplify the phenomenon of hate by attempting to label user comments as “hate” or “neutral”. This ignores the complex and subjective nature of HS, which limits the real-life applicability of classifiers trained on these corpora. In this study, we present the M-Phasis corpus, a corpus of ~9k German and French user comments collected from migration-related news articles. It goes beyond the “hate”-“neutral” dichotomy and is instead annotated with 23 features, which in combination become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of hate. The annotations are performed by 4 native speakers per language and achieve high (0.77 \textless= k \textless= 1) inter-annotator agreements. Besides describing the corpus creation and presenting insights from a content, error and domain analysis, we explore its data characteristics by training several classification baselines.</abstract>
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%0 Conference Proceedings
%T Placing M-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online
%A Ruiter, Dana
%A Reiners, Liane
%A D’Sa, Ashwin Geet
%A Kleinbauer, Thomas
%A Fohr, Dominique
%A Illina, Irina
%A Klakow, Dietrich
%A Schemer, Christian
%A Monnier, Angeliki
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F ruiter-etal-2022-placing
%X Even though hate speech (HS) online has been an important object of research in the last decade, most HS-related corpora over-simplify the phenomenon of hate by attempting to label user comments as “hate” or “neutral”. This ignores the complex and subjective nature of HS, which limits the real-life applicability of classifiers trained on these corpora. In this study, we present the M-Phasis corpus, a corpus of ~9k German and French user comments collected from migration-related news articles. It goes beyond the “hate”-“neutral” dichotomy and is instead annotated with 23 features, which in combination become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of hate. The annotations are performed by 4 native speakers per language and achieve high (0.77 \textless= k \textless= 1) inter-annotator agreements. Besides describing the corpus creation and presenting insights from a content, error and domain analysis, we explore its data characteristics by training several classification baselines.
%U https://aclanthology.org/2022.lrec-1.84
%P 791-804
Markdown (Informal)
[Placing M-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online](https://aclanthology.org/2022.lrec-1.84) (Ruiter et al., LREC 2022)
ACL
- Dana Ruiter, Liane Reiners, Ashwin Geet D’Sa, Thomas Kleinbauer, Dominique Fohr, Irina Illina, Dietrich Klakow, Christian Schemer, and Angeliki Monnier. 2022. Placing M-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 791–804, Marseille, France. European Language Resources Association.