The datafication of hate speech

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Hate speech has been identified as a pressing problem in society, and several automated approaches have been designed to detect and prevent it. This chapter reflects on the operationalizations, transformations, and reductions re- quired by the datafication of hate to build such an automated system. The obser- vations are based on an action research setting during a hate speech monitoring project conducted in a multi-organizational collaboration during the Finnish municipal elections in 2017. The project developed an adequately well-working algorithmic solution using supervised machine learning. However, the automa- ted approach requires heavy simplification, such as using rudimentary scales for classifying hate speech and relying on word-based approaches, while in reality hate speech is a nuanced linguistic and social phenomenon with various tones and forms. The chapter concludes by suggesting some practical implications for developing hate speech recognition systems.
Titel på värdpublikationChallenges and perspectives of hate speech research
RedaktörerChristian Strippel, Sünje Paasch-Colberg, Martin Emmer, Joachim Trebbe
Antal sidor18
FörlagFreie Universität Berlin
Utgivningsdatum17 apr. 2023
ISBN (elektroniskt)978-3-945681-12-1
StatusPublicerad - 17 apr. 2023
MoE-publikationstypA3 Del av bok eller annan forskningsbok


NamnDigital Communication Research
ISSN (elektroniskt)2198-7610


  • 518 Medie- och kommunikationsvetenskap
  • 5141 Sociologi

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