Abstract

Lists are essential elements of social media platforms: Lists of popular topics, accounts, followers, likes, clicks, views, search results or feeds provide orientation, structure our attention and guide practices of content reception and production. Content, they suggest, is particularly relevant when it is noticed by many, shared by many, commented by many. At the same time, researchers employ platform data and create lists themselves to approach issues, users or platform dynamics. The platforms’ logic of the many has inscribed itself in empirical platform research. Thereby, perspectives that move beyond the top users, the most used hashtags, the most shared URLs or the most active accounts are increasingly receding into the background. Inspired by discussions in data feminism (D’Ignazio/Klein 2020), we develop an alternative approach to Twitter/X data that questions how the platform aggregates diverse user activity into extrapolations of the many, by focusing on data that is not prominently displayed by the platform itself or even made invisible. We explore how platform data can be utilized to intervene into the data driven organizational logic of the platform itself.