Shadowbanning is a unique content moderation strategy receiving recent media attention for the ways it impacts marginalized social media users and communities. Social media companies often deny this content moderation practice despite user experiences online. In this paper, we first analyze previous platform responses to shadowbanning claims. We then use qualitative surveys and interviews to understand how marginalized social media users make sense of shadowbanning, develop folk theories about shadowbanning, and attempt to prove its occurrence. We also contribute collaborative algorithm investigation as a new strategy for social media users collaboratively developing and testing algorithmic folk theories.

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https://hci.top/en/papers/cscw/178495/2024

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DOI: https://dl.acm.org/doi/10.1145/3637431
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CSCW
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2024
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