论文标题
在线教授评论中检测客观的语言
Detecting Objectifying Language in Online Professor Reviews
论文作者
论文摘要
学生评论通常会引用教授的身体外观。直到最近，本研究重点的网站RatemyProfessor.com都使用了设计功能来鼓励大学教授的“热或不是热门”评级。在最近的#MeToo和#TimesUp运动之后，社会对这些评论的不适当的认识已经增强。但是，在此在线上下文中，客观评论仍保留并继续发布。我们描述了两个有监督的文本分类器，用于检测教授评论中的客观化评论。然后，我们整合了这些分类器，并使用结果模型按大规模跟踪客观的评论。我们在一个十年的时间段内衡量客观评论，评论网站接口的更改和教师性别之间的相关性。
Student reviews often make reference to professors' physical appearances. Until recently RateMyProfessors.com, the website of this study's focus, used a design feature to encourage a "hot or not" rating of college professors. In the wake of recent #MeToo and #TimesUp movements, social awareness of the inappropriateness of these reviews has grown; however, objectifying comments remain and continue to be posted in this online context. We describe two supervised text classifiers for detecting objectifying commentary in professor reviews. We then ensemble these classifiers and use the resulting model to track objectifying commentary at scale. We measure correlations between objectifying commentary, changes to the review website interface, and teacher gender across a ten-year period.
