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A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media. (arXiv:2307.06775v2 [cs.LG] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Over the last decade, there has been a vast increase in eating disorder
diagnoses and eating disorder-attributed deaths, reaching their zenith during
the Covid-19 pandemic. This immense growth derived in part from the stressors
of the pandemic but also from increased exposure to social media, which is rife
with content that promotes eating disorders. This study aimed to create a
multimodal deep learning model that can determine if a given social media post
promotes eating disorders based on a combination …
arxiv covid covid-19 covid-19 pandemic deep learning eating disorder growth identify media multimodal multimodal deep learning novel pandemic part social social media