Context-Aware Deep Markov Random Fields for Fake News Detection

Fake news is a serious problem, which has received considerable attention from both industry and academic communities. Over the past years, many fake news detection approaches have been introduced, and most of the existing methods rely on either news content or the social context of the news dissemi...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE access Vol. 9; pp. 130042 - 130054
Main Authors:	Huu Do, Tien, Berneman, Marc, Patro, Jasabanta, Bekoulis, Giannis, Deligiannis, Nikos
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks bias detection clickbait detection Context Correlation Data mining Deep learning Fake news detection Feature extraction Fields (mathematics) Linguistics Markov random field News question answering representation learning Representations sentiment analysis Social networking (online) Task analysis Toxicity toxicity detection Transformers
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!