Assessment of bidirectional transformer encoder model and attention based bidirectional LSTM language models for fake news detection-Reference-Cited by-同舟云学术

Assessment of bidirectional transformer encoder model and attention based bidirectional LSTM language models for fake news detection

Published:2024-01 Issue: Volume:76 Page:103545
ISSN:0969-6989
Container-title:Journal of Retailing and Consumer Services
language:en
Short-container-title:Journal of Retailing and Consumer Services

Author:

Choudhary Anshika^ORCID,Arora Anuja

Publisher

Elsevier BV

Subject

Marketing

Reference44 articles.

1. Stochastic numerical computing with Levenberg-Marquardt backpropagation for performance analysis of heat sink of functionally graded material of the porous fin;Ahmad;Surface. Interfac.,2021

2. Detection of online fake news using n-gram analysis and machine learning techniques;Ahmed,2017

3. Social media and fake news in the 2016 election;Allcott;J. Econ. Perspect.,2017

4. Context-based fake news detection model relying on deep learning models;Amer;Electronics,2022

5. Fake news detection using bi-directional LSTM-recurrent neural network;Bahad;Procedia Comput. Sci.,2019

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3. Deepfake technology amidst health emergencies: Discussing challenges, exploring opportunities, and charting strategic future paths (Preprint);2024-02-09

4. Modelling of a Non-Linear Dynamic System Using Long Short-Term Memory;2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2023-11-03