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dc.contributor.authorSouza, Garrett
dc.contributor.authorLutz, Nina
dc.contributor.authorTurner, Katlyn
dc.date.accessioned2025-09-29T20:14:24Z
dc.date.available2025-09-29T20:14:24Z
dc.date.issued2025-04-25
dc.identifier.isbn979-8-4007-1394-1
dc.identifier.urihttps://hdl.handle.net/1721.1/162829
dc.descriptionCHI ’25, Yokohama, Japanen_US
dc.description.abstractControl and curation of dominant visual culture – rendering who and what is visible – is central to identity formation, particularly for LGBTQ+ communities relying on digital spaces for safe self-expression. In this work, we analyze Instagram as a site of algorithmic visual curation, performing a quantitative analysis of algorithmically mediated image feeds delivered to a gay-coded user. Our persona account exclusively followed #gay and #instagay feeds, and engaged in content within these discursive spaces to seed algorithmic content promotion to a normative gay user. We present an analysis of skin tone presentations, emoji usage, and engagement metrics alongside analysis of generative outputs of dominant visual trends within the #gay search and Explore feeds. We observe content depicting darker-skinned individuals has higher engagement yet less algorithmic promotion relative to lighter skin tones, while hypermasculine and homonormative content is heavily promoted. These results suggest that, while marginalized positionalities have certainly been rendered more visible through social media platforms, this visibility is increasingly contingent on assimilation to normative ideals through algorithmically determined modes that are not necessarily consistent with user choices, preferences, or realities.en_US
dc.publisherACM|CHI Conference on Human Factors in Computing Systemsen_US
dc.relation.isversionofhttps://doi.org/10.1145/3706598.3713618en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleMediating The Marginal: A Quantitative Analysis of Curated LGBTQ+ Content on Instagramen_US
dc.typeArticleen_US
dc.identifier.citationGarrett Souza, Nina Lutz, and Katlyn M Turner. 2025. Mediating The Marginal: A Quantitative Analysis of Curated LGBTQ+ Content on Instagram. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 791, 1–20.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2025-08-01T08:09:32Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2025-08-01T08:09:33Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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