The datafication of hate speech

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


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.
Original languageEnglish
Title of host publicationChallenges and perspectives of hate speech research
EditorsChristian Strippel, Sünje Paasch-Colberg, Martin Emmer, Joachim Trebbe
Number of pages18
Place of PublicationBerlin
PublisherFreie Universität Berlin
Publication date17 Apr 2023
ISBN (Electronic)978-3-945681-12-1
Publication statusPublished - 17 Apr 2023
MoE publication typeA3 Book chapter

Publication series

NameDigital Communication Research
ISSN (Electronic)2198-7610

Fields of Science

  • 518 Media and communications
  • social media
  • hate
  • aggressiveness
  • speech
  • communication behavior
  • data access
  • 5141 Sociology
  • racism
  • sexism
  • antisemitism

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