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2020年美国民主党总统初选期间推特上的性别动态。

Gender dynamics on Twitter during the 2020 U.S. Democratic presidential primary.

作者信息

King Catherine, Carley Kathleen M

机构信息

Software and Societal Systems Department, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213 USA.

出版信息

Soc Netw Anal Min. 2023;13(1):50. doi: 10.1007/s13278-023-01045-4. Epub 2023 Mar 15.

Abstract

The Twitter social network for each of the top five U.S. Democratic presidential candidates in 2020 was analyzed to determine if there were any differences in the treatment of the candidates. This data set was collected from discussions of the presidential primary between December 2019 through April 2020. It was then separated into five sets,  one for each candidate. We found that the most discussed candidates, President Biden and Senator Sanders, received by far the most engagement from verified users and news agencies even before the Iowa caucuses, which was ultimately won by Mayor Buttigieg. The most popular candidates were also generally targeted more frequently by bots, trolls, and other aggressive users. However, the abusive language targeting the top two female candidates, Senators Warren and Klobuchar, included slightly more gendered and sexist language compared with the other candidates. Additionally, sexist slurs that ordinarily describe women were used more frequently than male slurs in all candidate data sets. Our results indicate that there may still be an undercurrent of sexist stereotypes permeating the social media conversation surrounding female U.S. presidential candidates.

摘要

对2020年美国民主党五位顶尖总统候选人各自的推特社交网络进行了分析,以确定对候选人的对待方式是否存在差异。该数据集收集自2019年12月至2020年4月期间总统初选的讨论内容。然后将其分为五组,每位候选人一组。我们发现,讨论最多的候选人拜登总统和桑德斯参议员,甚至在爱荷华州党团会议之前,就从认证用户和新闻机构那里获得了迄今为止最多的参与度,而最终赢得爱荷华州党团会议的是布蒂吉格市长。最受欢迎的候选人通常也更容易受到机器人、网络喷子和其他攻击性用户的频繁攻击。然而,针对两位女性候选人沃伦参议员和克洛布查尔参议员的辱骂性语言,与其他候选人相比,包含的性别歧视和性别主义语言略多。此外,在所有候选人的数据集中,通常描述女性的性别歧视诋毁性言辞比描述男性的使用得更频繁。我们的结果表明,在美国总统女性候选人的社交媒体对话中,可能仍然存在性别歧视刻板印象的暗流。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7317/10016153/3bcc2ba1e6c4/13278_2023_1045_Fig1_HTML.jpg

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