Understanding the Impact of Algorithmic Moderation on Social Networks a Digital Observation between Years 2023-2026 Visual Archive and Interviews using Content and Thematic Analyses
Year: 2026
Type: article
Abstract: Numerous studies examined algorithmic moderation (AM), but this study investigates its impact on users across social networks amidst a significant wave of digital censorship observed online and in prior literature since 2023. This qualitative thematic analysis (TA) study employed five phenomenological anonymous interviews of users affected by AM using snowball sampling, revealing eight themes. Most users shared terminologies, actions, and emotions related to the impact of AM across platforms. The repercussions of AM extended beyond online content removals, flags, and notices of violating Terms of Use which affected users with wrongful terminations, hiring freezes, and even instances of physical or verbal attacks. This is one of the first studies to list various types of AM and their impact on over 50 users with a visual data donation compiled until 2026 as timeline to allow pattern observation for future researches on online censorships, particularly towards the marginalized populations such as pro-Palestinians and Gaza PRESS journalists who were silenced. Human rights policies and ethical interventions like digital migrations, must be implemented with the international laws to detect bias or safeguard factual history online during the times of genocides, narrative control, internet blackouts, biased AM, and lack of users’ physical safety.
Author: Aniqa Afzal
Institution: University of Maryland, Baltimore County
Language: English
Subfield: Law
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225628239
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