City Research Online

Abstract

This paper contributes to the social media moderation research space by examining the still under-researched “shadowban”, a form of light and secret censorship targeting what Instagram defines as borderline content, particularly affecting posts depicting women’s bodies, nudity and sexuality. “Shadowban” is a user-generated term given to the platform’s “vaguely inappropriate content” policy, which hides users’ posts from its Explore page, dramatically reducing their visibility. While research has already focused on algorithmic bias and on social media moderation, there are not, at present, studies on how Instagram’s shadowban works. This autoethnographic exploration of the shadowban provides insights into how it manifests from a user’s perspective, applying a risk society framework to Instagram’s moderation of pole dancing content to show how the platform’s preventive measures are affecting user rights.

Publication Type:	Article
Additional Information:	© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Publisher Keywords:	Shadowban, Instagram, algorithm bias, pole dance, digital activism
Subjects:	H Social Sciences > HM Sociology T Technology > T Technology (General)
Departments:	School of Policy & Global Affairs > Sociology & Criminology
SWORD Depositor:	Symplectic Administrator

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