German (Ross et al. 2017), Hindi (Santosh and Aravind 2019), Indonesian
(Aulia and Budi 2019), Italian (Lingiardi et al. 2019), Korean (Kang et al.
2018), Polish (Czapla et al. 2019), Romanian (Meza 2016), and Spanish
(Basile et al. 2019). Crowd-sourced multilingual dictionaries of online hate
speech including Hatebase, the Racial Slur Database, and HateTrack have
also been developed, demonstrating promising avenues for future work
(ElSherief, Kulkarni et al. 2018, Siapera et al. 2018). Yet approaches to
automated hate speech detection that are designed to scale across multiple
languages are quite difﬁcult to develop, and more work is needed in this area.
Additionally, the majority of studies of online hate speech seek to detect all
types of hate speech at once, or “general hate speech” (Fortuna and Nunes
2018). However, other works have examined speciﬁc types of harmful
language, including jihadist hate speech (De Smedt et al. 2018), sectarian hate
Social_Media_and_Democracy