December 8, 2025Scientific ReportsOpen Access

Self-attention bidirectional long Short-Term memory assisted natural language processing on sarcasm detection and classification in social media platforms

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This analysis reveals improved sarcasm classification in social media using an automated model based on deep learning and Word2Vec.

Sarcasm classification achieved an accuracy of 94.45%, outperforming existing models.
Evaluation involved an automated model employing deep learning techniques for sarcasm detection.
Data preprocessing utilized Word2Vec for effective word embeddings in textual analysis.
Results suggest significant advancements in natural language processing for identifying sarcasm in social media.

Shouki A. Ebad (2025) studied this question.

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