IT University of Copenhagen sitecore@itu.dk https://video.itu.dk en-us Visualplatform http://blogs.law.harvard.edu/tech/rss IT University of Copenhagen Stay up to date with all the things that are happening at IT University of Copenhagen. This podcast will serve you various videos and audios with accounts from scientists and actual students at IT University, and give you a glimpse into their... episodic no https://video.itu.dk/files/rv0.0/sitelogo.gif https://video.itu.dk http://video.itu.dk/photo/70137820/annotating-online-misogyny <p>Philine Zeinert, Nanna Inie, and Leon Derczynski have created a powerful tool to identify and combat misogyny online.<br><br>Abstract:<br>Online misogyny, a category of online abusive language, has serious and harmful social consequences. Automatic detection of misogynistic language online, while imperative, poses complicated challenges to both data gathering, data annotation, and bias mitigation, as this type of data is linguistically complex and diverse. This paper makes three contributions in this area: Firstly, we describe the detailed design of our iterative annotation process and codebook. Secondly, we present a comprehensive taxonomy of labels for annotating misogyny in natural written language, and finally, we introduce a high-quality dataset of annotated posts sampled from social media posts. For more information:<br><br>&nbsp;<a href="https://www.derczynski.com/papers/annotating_online_misogyny.pdf">https://www.derczynski.com/papers/annotating_online_misogyny.pdf</a><br></p><p><a href="http://video.itu.dk/photo/70137820/annotating-online-misogyny"><img src="http://video.itu.dk/64968560/70137820/83276796ef66f8403a635ebb0409a458/standard/download-9-thumbnail.jpg" width="75" height=""/></a></p> http://video.itu.dk/photo/70137820 Tue, 27 Jul 2021 14:40:37 GMT Annotating Online Misogyny Philine Zeinert, Nanna Inie, and Leon Derczynski have created a powerful tool to identify and combat misogyny online.Abstract:Online misogyny, a category of online abusive language, has serious and harmful social consequences. Automatic detection of misogynistic language online, while imperative, poses complicated challenges to both data gathering, data annotation, and bias mitigation, as this type of data is linguistically complex and diverse. This paper makes three contributions in this area: Firstly, we describe the detailed design of our iterative annotation process and codebook. Secondly, we present a comprehensive taxonomy of labels for annotating misogyny in natural written language, and finally, we introduce a high-quality dataset of annotated posts sampled from social media posts. For more information:https://www.derczynski.com/papers/annotating_online_misogyny.pdf Philine Zeinert, Nanna Inie, and Leon Derczynski have created a powerful tool to identify and combat misogyny online.Abstract:Online misogyny, a category of online abusive language, has serious and harmful social consequences. Automatic detection... IT University of Copenhagen 04:30 <p>Philine Zeinert, Nanna Inie, and Leon Derczynski have created a powerful tool to identify and combat misogyny online.<br><br>Abstract:<br>Online misogyny, a category of online abusive language, has serious and harmful social consequences. Automatic detection of misogynistic language online, while imperative, poses complicated challenges to both data gathering, data annotation, and bias mitigation, as this type of data is linguistically complex and diverse. This paper makes three contributions in this area: Firstly, we describe the detailed design of our iterative annotation process and codebook. Secondly, we present a comprehensive taxonomy of labels for annotating misogyny in natural written language, and finally, we introduce a high-quality dataset of annotated posts sampled from social media posts. For more information:<br><br>&nbsp;<a href="https://www.derczynski.com/papers/annotating_online_misogyny.pdf">https://www.derczynski.com/papers/annotating_online_misogyny.pdf</a><br></p><p><a href="http://video.itu.dk/photo/70137820/annotating-online-misogyny"><img src="http://video.itu.dk/64968560/70137820/83276796ef66f8403a635ebb0409a458/standard/download-9-thumbnail.jpg" width="75" height=""/></a></p> algorithms misogyny online abuse