Features for Hate? Using the Delphi Method to Explore Digital Determinants for Online Hate Perpetration and Possibilities for Intervention.

Abstract

Online hate speech on social media platforms causes harm to those who are victimized as well as society at large. The prevalence of hateful content has, thus, prompted numerous calls for improved countermeasures and prevention. For such interventions to be effective, it is necessary to gain a nuanced understanding of influences that facilitate the spread of hate speech. This study does so by investigating what are relevant digital determinants for online hate perpetration. Moreover, the study explores possibilities of different technology-driven interventions for prevention. Thereby, the study specifically considers the digital environments in which online hate speech is most often produced and disseminated, namely social media platforms. We apply frameworks related to the concept of digital affordances to focus on the role that technological features of these platforms play in the context of online hate speech. Data were collected using the Delphi method in which a selected sample of experts from both research and practice answered multiple rounds of surveys with the goal of reaching a group consensus. The study encompassed an open-ended collection of initial ideas, followed by a multiple-choice questionnaire to identify, and rate the most relevant determinants. Usefulness of the suggested intervention ideas was assessed through the three lenses of human-centered design. The results of both thematic analysis and non-parametric statistics yield insights on how features of social media platforms can be both determinants that facilitate online hate perpetration as well as crucial mechanisms of preventive interventions. Implications of these findings for future intervention development are discussed.