Optimized Novel Text Embedding Approach for Fake News Detection on Twitter X: Integrating Social Context, Temporal Dynamics, and Enhanced Interpretability

Abstract In the era of widespread misinformation, detecting fake news has become a crucial challenge, particularly on social media platforms. This paper introduces an optimized approach for Fake News Detection, combining BERT and GloVe embeddings with Principal Component Analysis (PCA) and attention...

Full description

Saved in:

Bibliographic Details
Main Authors:	Mahmoud AlJamal, Rabee Alquran, Ayoub Alsarhan, Mohammad Aljaidi, Wafa’ Q. Al-Jamal, Ali Fayez Alkoradees
Format:	Article
Language:	English
Published:	Springer 2025-02-01
Series:	International Journal of Computational Intelligence Systems
Subjects:	Text Embedding Fake News Detection Twitter X BERT and GloVe Embeddings Attention Mechanisms SHAP and LIME
Online Access:	https://doi.org/10.1007/s44196-024-00730-2
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Optimized Novel Text Embedding Approach for Fake News Detection on Twitter X: Integrating Social Context, Temporal Dynamics, and Enhanced Interpretability

Similar Items