← Volume 12: Challenges and Perspectives of Hate Speech Research



Julian Risch

Berlin, 2023
DOI 10.48541/dcr.v12.13 (SSOAR)

Abstract: In research on online comments on social media platforms, different terms are widely used to describe comments that are hateful or disrespectful and thereby poison a discussion. This chapter takes a theoretical perspective on the term toxicity and related research in the field of computer science. More specifically, it explains the usage of the term and why its exact interpretation depends on the platform in question. Further, the article discusses the advantages of toxicity over other terms and provides an overview of the available toxic comment datasets. Finally, it introduces the concept of engaging comments as the counterpart of toxic comments, leading to a task that is complementary to the prevention and removal of toxic comments: the fostering and highlighting of engaging comments.


Julian Risch is a senior machine learning engineer at deepset.

Risch, J. (2023). Toxicity. In C. Strippel, S. Paasch-Colberg, M. Emmer, & J. Trebbe (Eds.), Challenges and perspectives of hate speech research (pp. 219–230). Digital Communication Research. https://doi.org/10.48541/dcr.v12.13

This book is published open access and licensed under Creative Commons Attribution 4.0 (CC-BY 4.0).
The persistent long-term archiving of this book is carried out with the help of the Social Science Open Access Repository and the university library of Freie Universität Berlin (Refubium).