Published : 2025-12-15

Shadow Banning: Between the “Ministry of Truth”, the ‘Secret Algorithm Police’ and a Strategy for Getting Knowledge about Users

Abstract

When, in 1993, the New Yorker posted a drawing of two dogs sitting in front of a computer screen with the humorous dialogue ‘On the Internet, no one knows you’re a dog,’ every reader knew that, although anonymity was involved, people were having the dialogue. There was no word about the role of the digital intermediary, and science had little to offer on the subject either. More than two decades later, the joke raises a sympathetic smile, but the attention of researchers is increasingly focused on ‘the third party’ – digital platforms that hold complex knowledge about users, although they themselves act as a non-transparent entity as to intentions and capabilities, ‘hidden in the screen’ setting the rules of behaviour and knowledge extraction on the platform.

The subject of the research presented here is shadow banning – a type of moderation that involves hiding/reducing the visibility of posts (users) from all users except the author. This is one of the most oppressive forms of interference by social media platforms.

The method of machine-supported systematic literature review adopted in the study allowed the identification not only of mainstream research on shadow banning, but the recognition of a research gap in the form of the relationship between shadow banning and algorithmic governance. In this perspective, shadow banning emerges not only as a complex, mysterious and oppressive form of platform interference, but as a deliberate action leading to the acquisition of knowledge about the limit of trust in platforms.

Keywords:

shadow banning, moderation, algorithmic management, social media platforms



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Kreft, J. (2025). Shadow Banning: Between the “Ministry of Truth”, the ‘Secret Algorithm Police’ and a Strategy for Getting Knowledge about Users. Roczniki Kulturoznawcze, 16(4), 13–34. https://doi.org/10.18290/rkult25164.2

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Roczniki Kulturoznawcze · ISSN 2082-8578 | eISSN 2544-5219 | DOI: 10.18290/rkult

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