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Graph convolution networks for social media trolls detection use deep feature extraction

Abstract This study presents a novel approach to identifying trolls and toxic content on social media using deep learning. We developed a machine-learning model capable of detecting toxic images through their embedded text content. Our approach leverages GloVe word embeddings to enhance the model's...

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Автори: Muhammad Asif, Muna Al-Razgan, Yasser A. Ali, Long Yunrong
Формат: Artigo
Мова:Inglês
Опубліковано: SpringerOpen 2024-02-01
Серія:Journal of Cloud Computing: Advances, Systems and Applications
Предмети:
Data mining
Digital forensics
Machine learning
Social media
Toxic data
Онлайн доступ:https://doi.org/10.1186/s13677-024-00600-4
Теги: Додати тег
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