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Quantifying gender biases towards politicians on Reddit

Despite attempts to increase gender parity in politics, global efforts have struggled to ensure equal female representation. This is likely tied to implicit gender biases against women in authority. In this work, we present a comprehensive study of gender biases that appear in online political discu...

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Detalles Bibliográficos
Autores principales: Marjanovic, Sara, Stańczak, Karolina, Augenstein, Isabelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603992/
https://www.ncbi.nlm.nih.gov/pubmed/36288326
http://dx.doi.org/10.1371/journal.pone.0274317
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author Marjanovic, Sara
Stańczak, Karolina
Augenstein, Isabelle
author_facet Marjanovic, Sara
Stańczak, Karolina
Augenstein, Isabelle
author_sort Marjanovic, Sara
collection PubMed
description Despite attempts to increase gender parity in politics, global efforts have struggled to ensure equal female representation. This is likely tied to implicit gender biases against women in authority. In this work, we present a comprehensive study of gender biases that appear in online political discussion. To this end, we collect 10 million comments on Reddit in conversations about male and female politicians, which enables an exhaustive study of automatic gender bias detection. We address not only misogynistic language, but also other manifestations of bias, like benevolent sexism in the form of seemingly positive sentiment and dominance attributed to female politicians, or differences in descriptor attribution. Finally, we conduct a multi-faceted study of gender bias towards politicians investigating both linguistic and extra-linguistic cues. We assess 5 different types of gender bias, evaluating coverage, combinatorial, nominal, sentimental and lexical biases extant in social media language and discourse. Overall, we find that, contrary to previous research, coverage and sentiment biases suggest equal public interest in female politicians. Rather than overt hostile or benevolent sexism, the results of the nominal and lexical analyses suggest this interest is not as professional or respectful as that expressed about male politicians. Female politicians are often named by their first names and are described in relation to their body, clothing, or family; this is a treatment that is not similarly extended to men. On the now banned far-right subreddits, this disparity is greatest, though differences in gender biases still appear in the right and left-leaning subreddits. We release the curated dataset to the public for future studies.
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spelling pubmed-96039922022-10-27 Quantifying gender biases towards politicians on Reddit Marjanovic, Sara Stańczak, Karolina Augenstein, Isabelle PLoS One Research Article Despite attempts to increase gender parity in politics, global efforts have struggled to ensure equal female representation. This is likely tied to implicit gender biases against women in authority. In this work, we present a comprehensive study of gender biases that appear in online political discussion. To this end, we collect 10 million comments on Reddit in conversations about male and female politicians, which enables an exhaustive study of automatic gender bias detection. We address not only misogynistic language, but also other manifestations of bias, like benevolent sexism in the form of seemingly positive sentiment and dominance attributed to female politicians, or differences in descriptor attribution. Finally, we conduct a multi-faceted study of gender bias towards politicians investigating both linguistic and extra-linguistic cues. We assess 5 different types of gender bias, evaluating coverage, combinatorial, nominal, sentimental and lexical biases extant in social media language and discourse. Overall, we find that, contrary to previous research, coverage and sentiment biases suggest equal public interest in female politicians. Rather than overt hostile or benevolent sexism, the results of the nominal and lexical analyses suggest this interest is not as professional or respectful as that expressed about male politicians. Female politicians are often named by their first names and are described in relation to their body, clothing, or family; this is a treatment that is not similarly extended to men. On the now banned far-right subreddits, this disparity is greatest, though differences in gender biases still appear in the right and left-leaning subreddits. We release the curated dataset to the public for future studies. Public Library of Science 2022-10-26 /pmc/articles/PMC9603992/ /pubmed/36288326 http://dx.doi.org/10.1371/journal.pone.0274317 Text en © 2022 Marjanovic et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Marjanovic, Sara
Stańczak, Karolina
Augenstein, Isabelle
Quantifying gender biases towards politicians on Reddit
title Quantifying gender biases towards politicians on Reddit
title_full Quantifying gender biases towards politicians on Reddit
title_fullStr Quantifying gender biases towards politicians on Reddit
title_full_unstemmed Quantifying gender biases towards politicians on Reddit
title_short Quantifying gender biases towards politicians on Reddit
title_sort quantifying gender biases towards politicians on reddit
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603992/
https://www.ncbi.nlm.nih.gov/pubmed/36288326
http://dx.doi.org/10.1371/journal.pone.0274317
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