男性当选，女性结婚：维基百科上的性别偏见事件
Men Are Elected, Women Are Married: Events Gender Bias on Wikipedia
摘要：
人类活动可以被视为一系列事件，这对理解社会至关重要。不同人口群体的不成比例的事件分布可以表现和放大社会陈规定型观念，并可能危及某些群体成员追求某些目标的能力。在本文中，我们提出了第一个以事件为中心的研究性别偏见的维基百科语料库。为了便于研究，我们策划了一个职业和个人生活描述的语料库，其中包含来自10，412位名人的7，854个片段。然后，我们用最先进的事件检测模型检测事件，使用策略生成的模板校准结果，并提取与性别有不对称关联的事件。我们的研究发现，维基百科的页面往往会将个人生活事件与女性的专业事件相结合，而不是男性，这需要维基百科社区的意识，以正式制定指导方针，并训练编辑注意贡献者所携带的隐性偏见。我们的工作也奠定了基础，为未来的工作量化和发现事件的偏见在语料库的水平。
英文摘要：
Human activities can be seen as sequences of events, which are crucial to understanding societies. Disproportional event distribution for different demographic groups can manifest and amplify social stereotypes, and potentially jeopardize the ability of members in some groups to pursue certain goals. In this paper, we present the first event-centric study of gender biases in a Wikipedia corpus. To facilitate the study, we curate a corpus of career and personal life descriptions with demographic information consisting of 7,854 fragments from 10,412 celebrities. Then we detect events with a state-of-the-art event detection model, calibrate the results using strategically generated templates, and extract events that have asymmetric associations with genders. Our study discovers that the Wikipedia pages tend to intermingle personal life events with professional events for females but not for males, which calls for the awareness of the Wikipedia community to formalize guidelines and train the editors to mind the implicit biases that contributors carry. Our work also lays the foundation for future works on quantifying and discovering event biases at the corpus level.
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。
