Misogyny Detection in Twitter: a Multilingual and Cross-Domain Study
Information Processing & Management(2020)
摘要
•We conduct a broad and in-depth study on online misogyny, a relevant and timely task given that more and more episodes of hate speech and online harassment happen in social media.•An extensive review of the state of the art in misogyny detection is presented.•A state-of-the-art model to detect misogyny in social media is developed, and evaluated on three different languages, English, Italian, and Spanish.•We investigate the most predictive linguistic features to distinguish misogynistic content from not-misogynistic content.•Relationships between misogyny and other abusive language phenomena are postulated, and empirically investigated with cross-dataset experiments.•The feasibility of detecting misogyny in a multilingual environment is explored.
更多查看译文
关键词
Automatic misogyny identification,Abusive language online,Cross-domain classification,Cross-lingual classification,Social media
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络