Web of things based social media fake news classification with feature extraction using pre-trained convoluted recurrent network with deep fuzzy learning-Reference-Cited by-同舟云学术

Web of things based social media fake news classification with feature extraction using pre-trained convoluted recurrent network with deep fuzzy learning

Published:2022-09 Issue: Volume:931 Page:65-77
ISSN:0304-3975
Container-title:Theoretical Computer Science
language:en
Short-container-title:Theoretical Computer Science

Author:

Li Tingyu,Yu Jing,Zhang Haiping

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference22 articles.

1. FNDNet–A deep convolutional neural network for fake news detection;Kaliyar;Cogn. Syst. Res.,2020

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

3. Analysis of classifiers for fake news detection;Agarwal;Proc. Comput. Sci.,2019

4. Detecting fake news to reduce misinformation risks using analytics approaches;Zhang;Eur. J. Oper. Res.,2019

5. Fake news identification and classification using DSSM and improved recurrent neural network classifier;Jadhav;Appl. Artif. Intell.,2019

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