Abstract

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The presence of openly non-binary gender individuals on social networks is growing. However, the relationship between gender, activity, and language in online interactions has not been extensively explored. Lack of understanding surrounding this interaction can result in the disparate treatment of non-binary gender individuals on online platforms. We investigate patterns of gender-based behavior identity on Twitter, focusing on gender expression as represented by users’ expression of pronouns from eight different pronoun groups. We find that non-binary gender groups tend to receive substantially less attention in the form of likes and followers compared to binary groups. Additionally, non-binary users send and receive tweets with higher toxicity scores than other groups. This study identifies differences in the language and online activity of users with non-binary gender identity, and highlights a need for further …

Metadata

publication

International Conference on Advances in Social Networks Analysis and Mining …, 2024

year

2024

publication date

2024/9/2

authors

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

link

https://link.springer.com/chapter/10.1007/978-3-031-78538-2_7

resource_link

https://arxiv.org/pdf/2303.04837

book

International Conference on Advances in Social Networks Analysis and Mining

pages

85-95

publisher

Springer Nature Switzerland