Let’s (re)tweet about racism and sexism: responses to cyber aggression toward Black and Asian women

Online, anyone’s words can easily be amplified – and on Twitter, the platform’s algorithm highlights tweets that gain attention from other users, which can exponentially reinforce a tweet’s popularity. Moreover, retweets can help spread a message well beyond the reach of its original poster. Thus, users’ interactions with posts containing or making reference to racism or sexism both illuminate the ways individuals accept, challenge, or engage with racism and sexism online, and shape how those messages spread. Using an original dataset of 59.5 million tweets, I test how particular features of messages referencing Black and Asian women predict user engagement (retweets, likes, and replies). This analysis further focuses on messages including terms that express racist or sexist content. Generally, messages including covert racist or sexist insults have a modest positive effect on all measures of user engagement (retweets, likes, and replies), which may suggest that social media environments allow individuals the time and opportunity to contend with topics that can be more difficult in-person. Additionally, variations in engagement with tweets that include references to women, Black or Asian individuals implies that users respond differently to messages involving references to and normative images of different racial, ethnic, and gendered identities. This research illuminates how specific manifestations of racialized and gendered language referencing women, Black and Asian people can not only encourage more engagement, but also share, accept, or challenge messages about marginalized identities.在网络空间中，任何人的言论都极易被放大；在推特（Twitter）平台上，其算法会优先推送获得其他用户关注的推文，这会以指数级态势强化单条推文的传播热度。此外，转发功能可让信息的传播范围远超原发布者的触达边界。因此，用户对包含或提及种族主义、性别主义内容的帖文的互动行为，既能揭示个体在网络空间中接纳、驳斥或参与种族主义与性别主义言论的具体方式，也会影响此类信息的传播轨迹。本研究基于包含5950万条推文的原创数据集，探究提及黑人和亚裔女性的言论的特定特征如何影响用户互动行为（转发、点赞与回复）。本次分析进一步聚焦于包含种族主义或性别主义表述的言论。总体而言，包含隐晦种族主义或性别主义攻击性表述的言论，对用户互动的各项指标（转发、点赞与回复）均存在适度正向影响，这或许意味着社交媒体环境为个体提供了应对线下场景中更难直面的议题的时间与契机。此外，针对提及女性、黑人或亚裔个体的推文的互动差异表明，用户对涉及不同种族、族裔与性别身份的表述及其刻板印象形象的回应方式存在显著区别。本研究揭示了针对女性、黑人和亚裔群体的种族化与性别化语言的特定表现形式，不仅能提升用户互动度，更可推动边缘化身份相关言论的传播、接纳或驳斥。