The Devil is in the Detail: Reconceptualizing Bystander Reactions to Online Hate Speech

Twitter’s decision to suspend the account of Donald Trump for incitement of violence in the aftermath of the Capitol Hill attack was noted with great interest around the world. It raised questions as to how best to handle moderation of hateful content in the online sphere, and sparked debate about the potential undesired effects on freedom of speech of the take-down approach commonly employed by social media sites. Counter speech and other types of pro-social bystander behaviors (E.g., reporting, counterarguing, ranking) present valuable alternative approaches to suspension. They rely on the reactions of online bystanders and enable the hateful content to remain available. These features are not only valuable as the crowd-sourced moderation enables broader reach; they also enable the hateful content to remain part of the debate, circumventing the issues raised by platform administered censorship, while mediating some of the negative impacts on onlookers caused by the hateful content. The jury is still out as to the potential, and magnitude, of positive effects affiliated with pro-social bystander reactions, yet this may not be the only pertinent issue facing this research agenda. Because what does a pro-social bystander reaction actually entail? What do such reactions look like (forms); what different functions are they intended to serve (types); and who is the communication aimed at (receiver)? In this paper, I dabble with the very conceptualization of pro-social bystander reactions, as I rethink the prevailing binary “takes place / does not take place” conceptualization. I do this in three steps. First, I review the existing literature for definitions and operationalizations of online bystander reactions – noting the many names this phenomenon goes by in the process. Second, I synthesize the existing conceptualizations and propose a new layered approach to thinking about online bystander reactions. Lastly, I discuss the implications of utilizing this non-binary understanding of bystander reactions to the study of, and fight against, online hate speech.