Algorithmic ethnography, during and after COVID-19

Abstract

Social scientists are increasingly turning to digital interactions as a primary source of qualitative data. Online activities in turn typically take place on algorithmically mediated platforms, which shape what people do and say in crucial ways. Here, I offer a toolkit for what I call algorithmic ethnography, that is, the ethnographic study of how computational systems structure online activities. First, scholars need to follow the data and take into consideration the tracking strategies, monetization systems, and business models of the platforms where online interactions unfold. Second, ethnographers should focus on the details of algorithmic sorting, since platforms typically have more content than they can display and thus rely on algorithmic procedures to personalize their pages. Third, ethnographers should include metrics in their fieldwork and study their effects on interactions, hierarchies, and representations. Together, these angles afford a fine-grained understanding of the computational texture of online exchanges.