Unveiling Gender Dynamics for Mental Health Posts in Social Media and Generative Artificial Intelligence

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dc.contributor.authorMattson, Tom
dc.contributor.authorWeng, Qin
dc.contributor.authorRen, Jie
dc.date.accessioned2024-12-26T21:10:21Z
dc.date.available2024-12-26T21:10:21Z
dc.date.issued2025-01-07
dc.description.abstractWe investigate the level of empathy mental health posts receive on social media and generative artificial intelligence (GenAI). Specifically, we examine gender effects to determine if posts authored by self-identified men, women, or unknown (no self-identified gender discloser) receive varying levels of empathy across different technical platforms. Using a sample of mental health posts from Reddit, we find that self-identified women receive more empathy relative to men across all platforms. We further find that Inflection Pi, a GenAI tool specifically designed to be empathetic, provides the most empathy, but it still favors self-identified women over men. Self-identified men attempting to receive empathy for their prolonged emotional distress are disadvantaged relative to self-identified women.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2025.784
dc.identifier.isbn978-0-9981331-8-8
dc.identifier.other44463cfd-0186-463f-8227-e69f41ba4bad
dc.identifier.urihttps://hdl.handle.net/10125/109632
dc.relation.ispartofProceedings of the 58th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBright and Dark Side of Social Media in the Marginalized Contexts
dc.subjectempathy, gender effects, generative artificial intelligence, mental health, social media
dc.titleUnveiling Gender Dynamics for Mental Health Posts in Social Media and Generative Artificial Intelligence
dc.typeConference Paper
dc.type.dcmiText
prism.startingpage6557

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Bright and Dark Side of Social Media in the Marginalized Contexts