Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study
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| Title: | Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community–Related Posts on Social Media: Quantitative Study |
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| Authors: | Nguyen, Thu T1, ttxn@umd.edu, Yue, Xiaohe1, Mane, Heran1, Seelman, Kyle2, Mullaputi, Penchala Sai Priya1, Dennard, Elizabeth1, Alibilli, Amrutha S1, Merchant, Junaid S1, Criss, Shaniece3, Hswen, Yulin4, Nguyen, Quynh C1 |
| Source: | Journal of Medical Internet Research; 2025, Vol. 27, p1-19, 19p |
| Database: | Applied Science & Technology Source |
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