ALGORITHMIC JUSTICE FROM BELOW

Authors

  • Aikaterini Mniestri University of Siegen
  • Sebastian Randerath Rheinische Friedrich-Wilhelms-Universität Bonn

DOI:

https://doi.org/10.5210/spir.v2022i0.13055

Keywords:

algorithmic gossip, platform governance, tracking, intersectionality, social media

Abstract

Tracking has become an integral part of users’ social media experience and the political economy of platforms. Creator studios are part of a larger assemblage of machine-readable metrics and data analytics on the back end of a digital platform. While it has become common practice for creators to make use of this feature to grow their business, creators have also appropriated it to engage collectively in “algorithmic gossip” around social issues. We observe how algorithmic gossip can become instrumental in the hands of minoritized groups. Particularly, following the Black Lives Matter protests in 2020, creators noticed that their posts were less visible after using platforms to report on the movement. As more and more creators took screenshots of their analytics and posted them, they were able to force a response out of the company. In response, Tik Tok launched an incubator to boost talent from the black community. Thereby, the company made a commitment “to elevate and amplify their voices”. In this paper we ask: Does algorithmic gossip about tracking provide a basis for overcoming algorithmic oppression or is it incorporated for hegemonic strategies of platform governance and silencing? We argue that end users gather insights from the analytics on the creator studio to reveal patterns of algorithmic injustice and bias. In the second part, we argue that platform companies undermine the collective struggle of minoritized groups through self-governance. As a result, we contend that this case study legitimizes arguments in the discourse against the self-governance of platform companies.

Downloads

Published

2023-03-30

How to Cite

Mniestri, A., & Randerath, S. (2023). ALGORITHMIC JUSTICE FROM BELOW. AoIR Selected Papers of Internet Research, 2022. https://doi.org/10.5210/spir.v2022i0.13055

Issue

Section

Papers M