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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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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. |
format | Online Article Text |
id | pubmed-10235607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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