An inter-modal attention-based deep learning framework using unified modality for multimodal fake news, hate speech and offensive language detection

Fake news, hate speech and offensive language are related evil triplets currently affecting modern societies. Text modality for the computational detection of these phenomena has been widely used. In recent times, multimodal studies in this direction are attracting a lot of interests because of the...

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Veröffentlicht in:	Information systems (Oxford) Jg. 123; S. 102378
Hauptverfasser:	Ayetiran, Eniafe Festus, Özgöbek, Özlem
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2024
Schlagworte:	BiLSTM-CNN Fake news Hate speech Inter-modal attention Multimodal content understanding Multimodal fusion Offensive language Unified modality Inter-modal attention Unified modality BiLSTM-CNN Hate speech Multimodal fusion Offensive language Fake news Multimodal content understanding
ISSN:	0306-4379, 1873-6076
Online-Zugang:	Volltext
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