In recent years, several computational tools have been developed to detect and identify sexism, misogyny, and gender-based hate speech, especially on online platforms. Though these tools intend to draw on knowledge from both social science and computer science, little is known about the current state of research in quantifying online sexism or misogyny. Given the growing concern over the discrimination of women in online spaces and the rise in interdisciplinary research on capturing the online manifestation of sexism and misogyny, a systematic literature review on the research practices and their measures is the need of the hour. We make three main contributions: (i) we present a semi-automated way to narrow down the search results in the different phases of selection stage in the PRISMA flowchart; (ii) we perform a systematic literature review of research papers that focus on the quantification and measurement of online gender-based hate speech, examining literature from computer science and the social sciences from 2012 to 2022; and (iii) we identify the opportunities and challenges for measuring gender-based online hate speech. Our findings from topic analysis suggest a disciplinary divide between the themes of research on sexism/misogyny. With evidence-based review, we summarise the different approaches used by the studies who have explored interdisciplinary approaches to bridge the knowledge gap. Coupled with both the existing literature on social science theories and computational modeling, we provide an analysis of the benefits and shortcomings of the methodologies used. Lastly, we discuss the challenges and opportunities for future research dedicated to measuring online sexism and misogyny.

本研究解决了对在线性别歧视和厌女症量化研究现状了解不足的问题，提出了一种半自动化的方法，以优化PRISMA流程图中的选择阶段。此外，通过对2012年至2022年相关文献的系统综述，研究揭示了社会科学与计算机科学中对性别基础仇恨言论量化的机会与挑战。研究结果显示出学科间的主题分歧，对未来介于两者之间的研究方向提供了启示。

学科划分？对在线性别歧视和厌女症量化的系统文献综述