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During the coronavirus pandemic, woman-led countries had significantly better outcomes (in terms of number of deaths) than comparable male-led countries. Recent years have induced a wave of female politicians entering office in the United States and Europe, including the first female US Vice-President (after 6 failed female presidential bids that year).

These datasets are a subset of the already publicly available Pushshift dataset created using the official Reddit API with some additional Wikidata-sourced information regarding the mentioned politicians.įunding: (IA) This work is partly funded by Independent Research Fund Denmark under grant agreement number 9130-00092B.Ĭompeting interests: The authors have declared that no competing interests exist.

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However, the full data-set is available on the Harvard Dataverse (Replication Data for: Quantifying gender biases towards politicians on Reddit).

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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: A minimal representation of the data-set (Reddit comment ID and linked Wikidata ID) is presented on GitHub due to file size constraints of Github, along with the code used (GitHub - spaidataiga/RedditPoliticalBias: The data and code used in the production of my Master’s thesis). Received: DecemAccepted: AugPublished: October 26, 2022Ĭopyright: © 2022 Marjanovic et al. We release the curated dataset to the public for future studies.Ĭitation: Marjanovic S, Stańczak K, Augenstein I (2022) Quantifying gender biases towards politicians on Reddit. 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. 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.

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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. Overall, we find that, contrary to previous research, coverage and sentiment biases suggest equal public interest in female politicians. We assess 5 different types of gender bias, evaluating coverage, combinatorial, nominal, sentimental and lexical biases extant in social media language and discourse. Finally, we conduct a multi-faceted study of gender bias towards politicians investigating both linguistic and extra-linguistic cues. 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. 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. In this work, we present a comprehensive study of gender biases that appear in online political discussion. This is likely tied to implicit gender biases against women in authority.

Despite attempts to increase gender parity in politics, global efforts have struggled to ensure equal female representation.