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arXiv 2303.04837cs.SI
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在线互动中的非二元性别表达

Non-Binary Gender Expression in Online Interactions

Rebecca Dorn, Negar Mokhberian, Julie Jiang, Jeremy Abramson, Fred Morstatter, Kristina Lerman

AI总结:

本研究探讨了Twitter上非二元性别个体的在线互动,发现其在点赞和关注者上获关注较少,且推文毒性较高,强调应将性别视为谱系以理解在线表达。

摘要:

许多公开的非二元性别个体参与社交网络。然而,性别与在线互动之间的关系尚不清楚,这可能导致大型语言模型产生差异化对待。我们调查了Twitter上的个体身份,重点关注用户所选代词所代表的性别表达。我们发现非二元群体往往在点赞和关注者方面获得的关注较少。我们还发现非二元用户发送和接收的推文具有高于平均水平的毒性。该研究强调了在理解在线互动和表达时,将性别视为一个谱系而非二元的重要性。

英文摘要:

Many openly non-binary gender individuals participate in social networks. However, the relationship between gender and online interactions is not well understood, which may result in disparate treatment by large language models. We investigate individual identity on Twitter, focusing on gender expression as represented by users chosen pronouns. We find that non-binary groups tend to receive less attention in the form of likes and followers. We also find that nonbinary users send and receive tweets with above-average toxicity. The study highlights the importance of considering gender as a spectrum, rather than a binary, in understanding online interactions and expression.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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