Position-context additive transformer-based model for classifying text data on social media

Position-context additive transformer-based model for classifying text data on social media

Abstract In recent years, the continuous increase in the growth of text data on social media has been a major reason to rely on the pre-training method to develop new text classification models specially transformer-based models that have proven worthwhile in most natural language processing tasks....

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Bibliographic Details
Main Authors: M. M. Abd-Elaziz, Nora El-Rashidy, Ahmed Abou Elfetouh, Hazem M. El-Bakry
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Social media
Transformer-based model
Word embedding
Bi-LSTM network
Additive attention
Online Access:https://doi.org/10.1038/s41598-025-90738-1
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https://doi.org/10.1038/s41598-025-90738-1

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