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Who are the haters? A corpus-based demographic analysis of authors of hate speech

INTRODUCTION: We examine the profiles of hate speech authors in a multilingual dataset of Facebook reactions to news posts discussing topics related to migrants and the LGBT+ community. The included languages are English, Dutch, Slovenian, and Croatian. METHODS: First, all utterances were manually a...

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Autores principales: Hilte, Lisa, Markov, Ilia, Ljubešić, Nikola, Fišer, Darja, Daelemans, Walter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235607/
https://www.ncbi.nlm.nih.gov/pubmed/37275533
http://dx.doi.org/10.3389/frai.2023.986890
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author Hilte, Lisa
Markov, Ilia
Ljubešić, Nikola
Fišer, Darja
Daelemans, Walter
author_facet Hilte, Lisa
Markov, Ilia
Ljubešić, Nikola
Fišer, Darja
Daelemans, Walter
author_sort Hilte, Lisa
collection PubMed
description INTRODUCTION: We examine the profiles of hate speech authors in a multilingual dataset of Facebook reactions to news posts discussing topics related to migrants and the LGBT+ community. The included languages are English, Dutch, Slovenian, and Croatian. METHODS: First, all utterances were manually annotated as hateful or acceptable speech. Next, we used binary logistic regression to inspect how the production of hateful comments is impacted by authors' profiles (i.e., their age, gender, and language). RESULTS: Our results corroborate previous findings: in all four languages, men produce more hateful comments than women, and people produce more hate speech as they grow older. But our findings also add important nuance to previously attested tendencies: specific age and gender dynamics vary slightly in different languages or cultures, suggesting that distinct (e.g., socio-political) realities are at play. DISCUSSION: Finally, we discuss why author demographics are important in the study of hate speech: the profiles of prototypical “haters” can be used for hate speech detection, for sensibilization on and for counter-initiatives to the spread of (online) hatred.
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spelling pubmed-102356072023-06-03 Who are the haters? A corpus-based demographic analysis of authors of hate speech Hilte, Lisa Markov, Ilia Ljubešić, Nikola Fišer, Darja Daelemans, Walter Front Artif Intell Artificial Intelligence INTRODUCTION: We examine the profiles of hate speech authors in a multilingual dataset of Facebook reactions to news posts discussing topics related to migrants and the LGBT+ community. The included languages are English, Dutch, Slovenian, and Croatian. METHODS: First, all utterances were manually annotated as hateful or acceptable speech. Next, we used binary logistic regression to inspect how the production of hateful comments is impacted by authors' profiles (i.e., their age, gender, and language). RESULTS: Our results corroborate previous findings: in all four languages, men produce more hateful comments than women, and people produce more hate speech as they grow older. But our findings also add important nuance to previously attested tendencies: specific age and gender dynamics vary slightly in different languages or cultures, suggesting that distinct (e.g., socio-political) realities are at play. DISCUSSION: Finally, we discuss why author demographics are important in the study of hate speech: the profiles of prototypical “haters” can be used for hate speech detection, for sensibilization on and for counter-initiatives to the spread of (online) hatred. Frontiers Media S.A. 2023-05-19 /pmc/articles/PMC10235607/ /pubmed/37275533 http://dx.doi.org/10.3389/frai.2023.986890 Text en Copyright © 2023 Hilte, Markov, Ljubešić, Fišer and Daelemans. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Hilte, Lisa
Markov, Ilia
Ljubešić, Nikola
Fišer, Darja
Daelemans, Walter
Who are the haters? A corpus-based demographic analysis of authors of hate speech
title Who are the haters? A corpus-based demographic analysis of authors of hate speech
title_full Who are the haters? A corpus-based demographic analysis of authors of hate speech
title_fullStr Who are the haters? A corpus-based demographic analysis of authors of hate speech
title_full_unstemmed Who are the haters? A corpus-based demographic analysis of authors of hate speech
title_short Who are the haters? A corpus-based demographic analysis of authors of hate speech
title_sort who are the haters? a corpus-based demographic analysis of authors of hate speech
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235607/
https://www.ncbi.nlm.nih.gov/pubmed/37275533
http://dx.doi.org/10.3389/frai.2023.986890
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