Cognitive assemblages: The entangled nature of algorithmic content moderation - Sciences Po Access content directly
Journal Articles Big Data & Society Year : 2022

Cognitive assemblages: The entangled nature of algorithmic content moderation

Valentine Crosset
Benoît Dupont
  • Function : Author
  • PersonId : 1120328


This article examines algorithmic content moderation, using the moderation of violent extremist content as a specific case. In recent years, algorithms have increasingly been mobilized to perform essential moderation functions for online social media platforms such as Facebook, YouTube, and Twitter, including limiting the proliferation of extremist speech. Drawing on Katherine Hayles’ concept of “cognitive assemblages” and the Critical Security Studies literature, we show how algorithmic regulation operates within larger assemblages of humans and non-humans to influence the surveillance and regulation of information flows. We argue that the dynamics of algorithmic regulation are more liquid, cobbled together and distributed than it appears. It is characterized by a set of shifting human and machine entities, which mix traditional surveillance methods with more sophisticated tools, and whose linkages and interactions are transient. The processes that enable the consolidation of knowledge about risky profiles and contents are, therefore, collective and distributed among humans and machines. This allows us to argue that the cognitive assemblages involved in content moderation become a cobbled space of preemptive calculation.
Fichier principal
Vignette du fichier
Crosset and Dupont-Cognitive assemblages.pdf (602 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Licence : CC BY NC - Attribution - NonCommercial

Dates and versions

hal-03960156 , version 1 (27-01-2023)


Attribution - NonCommercial



Valentine Crosset, Benoît Dupont. Cognitive assemblages: The entangled nature of algorithmic content moderation. Big Data & Society, 2022, 9 (2), ⟨10.1177/20539517221143361⟩. ⟨hal-03960156⟩
43 View
113 Download



Gmail Facebook X LinkedIn More