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首页> 外文期刊>Information Processing & Management >A little bird told me your gender: Gender inferences in social media
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A little bird told me your gender: Gender inferences in social media

机译：一只小鸟告诉我你的性别：社交媒体的性别推论

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摘要

Online and social media platforms employ automated recognition methods to presume user preferences, sensitive attributes such as race, gender, sexual orientation, and opinions. These opaque methods can predict behaviors for marketing purposes and influence behavior for profit, serving attention economics but also reinforcing existing biases such as gender stereotyping. Although two international human rights treaties include explicit obligations relating to harmful and wrongful stereotyping, these stereotypes persist online and offline. By identifying how inferential analytics may reinforce gender stereotyping and affect marginalized communities, opportunities for addressing these concerns and thereby increasing privacy, diversity, and inclusion online can be explored. This is important because misgendering reinforces gender stereotypes, accentuates gender binarism, undermines privacy and autonomy, and may cause feelings of rejection, impacting people's self-esteem, confidence, and authenticity. In turn, this may increase social stigmatization. This study brings into view concerns of discrimination and exacerbation of existing biases that online platforms continue to replicate and that literature starts to highlight. The implications of misgendering on Twitter are investigated to illustrate the impact of algorithmic bias on inadvertent privacy violations and reinforcement of social prejudices of gender through a multidisciplinary perspective, including legal, computer science, and critical feminist media-studies viewpoints. An online pilot survey was conducted to better understand how accurate Twitter's gender inferences of its users' gender identities are. This served as a basis for exploring the implications of this social media practice.
机译：网络和社交媒体平台采用自动识别方法推定用户的喜好，敏感的属性，如种族，性别，性取向，和意见。这些不透明的方法可以预测的行为出于营销目的和影响力的行为以盈利为目的，服务注意经济也加强现有的偏见，如性别成见。尽管两项国际人权条约包括与有害的和非法的成见明确的义务，这些成见坚持在线和离线。通过确定如何推理分析可能加强性别成见和影响边缘化的社区，机会解决这些问题，从而增加了私密性，多样性和包容性网上可以探讨。这很重要，因为misgendering强化性别刻板印象，性别展露无遗binarism，破坏隐私权和自主权，并可能引起排斥反应的感情，影响人的自尊，自信和真实性。反过来，这可能会增加社会歧视。这项研究带来眼帘的歧视和偏见存在，网上平台继续复制的恶化的担忧和文学开始的亮点。 misgendering在Twitter上的影响进行了研究，通过多学科的角度，包括法律，计算机科学和关键女权主义媒介研究的观点来说明算法偏差的误侵犯隐私和性别的社会偏见的增强的影响。在线试点调查，以进行更好地了解用户的性别认同Twitter的性别推断如何准确的。这曾担任探索这个社会化媒体实践的影响的基础。

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