%0 Conference Proceedings %T Targets and Aspects in Social Media Hate Speech %A Shvets, Alexander %A Fortuna, Paula %A Soler, Juan %A Wanner, Leo %Y Mostafazadeh Davani, Aida %Y Kiela, Douwe %Y Lambert, Mathias %Y Vidgen, Bertie %Y Prabhakaran, Vinodkumar %Y Waseem, Zeerak %S Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021) %D 2021 %8 August %I Association for Computational Linguistics %C Online %F shvets-etal-2021-targets %X Mainstream research on hate speech focused so far predominantly on the task of classifying mainly social media posts with respect to predefined typologies of rather coarse-grained hate speech categories. This may be sufficient if the goal is to detect and delete abusive language posts. However, removal is not always possible due to the legislation of a country. Also, there is evidence that hate speech cannot be successfully combated by merely removing hate speech posts; they should be countered by education and counter-narratives. For this purpose, we need to identify (i) who is the target in a given hate speech post, and (ii) what aspects (or characteristics) of the target are attributed to the target in the post. As the first approximation, we propose to adapt a generic state-of-the-art concept extraction model to the hate speech domain. The outcome of the experiments is promising and can serve as inspiration for further work on the task %R 10.18653/v1/2021.woah-1.19 %U https://aclanthology.org/2021.woah-1.19 %U https://doi.org/10.18653/v1/2021.woah-1.19 %P 179-190