SA-Bi-LSTM: Self Attention With Bi-Directional LSTM-Based Intelligent Model for Accurate Fake News Detection to Ensured Information Integrity on Social Media Platforms-Reference-Cited by-同舟云学术

SA-Bi-LSTM: Self Attention With Bi-Directional LSTM-Based Intelligent Model for Accurate Fake News Detection to Ensured Information Integrity on Social Media Platforms

Published:2024 Issue: Volume:12 Page:48436-48452
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Jian Wang¹,Li Jian Ping²^ORCID,Akbar Muhammad Atif³,Haq Amin Ul²^ORCID,Khan Shakir⁴^ORCID,Alotaibi Reemiah Muneer⁴,Alajlan Saad Abdullah⁴

Affiliation:

1. School of Artificial Intelligence, Neijiang Normal University, Neijiang, Sichuan, China

2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

3. Computer Science Department, Mohi-Ud-Din Islamic University, Nerian Sharif, Azad Kashmir, Pakistan

4. College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

Funder

Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10483072.pdf?arnumber=10483072

Reference31 articles.

1. Fake news detection: Taxonomy and comparative study

2. BERT: Pre-training of deep bidirectional transformers for language understanding;Devlin;arXiv:1810.04805,2018

3. A Novel Stacking Approach for Accurate Detection of Fake News

4. An overview of online fake news: Characterization, detection, and discussion

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