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Article

Deep Learning for Fake News Detection in a Pairwise Textual Input Schema

Department of Informatics, Ionian University, 49100 Corfu, Greece
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Yudong Zhang
Received: 31 December 2020 / Revised: 12 February 2021 / Accepted: 12 February 2021 / Published: 17 February 2021
(This article belongs to the Special Issue Recent Advances in Computation Engineering)
In the past decade, the rapid spread of large volumes of online information among an increasing number of social network users is observed. It is a phenomenon that has often been exploited by malicious users and entities, which forge, distribute, and reproduce fake news and propaganda. In this paper, we present a novel approach to the automatic detection of fake news on Twitter that involves (a) pairwise text input, (b) a novel deep neural network learning architecture that allows for flexible input fusion at various network layers, and (c) various input modes, like word embeddings and both linguistic and network account features. Furthermore, tweets are innovatively separated into news headers and news text, and an extensive experimental setup performs classification tests using both. Our main results show high overall accuracy performance in fake news detection. The proposed deep learning architecture outperforms the state-of-the-art classifiers, while using fewer features and embeddings from the tweet text. View Full-Text
Keywords: fake news detection; deception detection; machine learning; natural language processing; deep learning; social media; pairwise input fake news detection; deception detection; machine learning; natural language processing; deep learning; social media; pairwise input
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MDPI and ACS Style

Mouratidis, D.; Nikiforos, M.N.; Kermanidis, K.L. Deep Learning for Fake News Detection in a Pairwise Textual Input Schema. Computation 2021, 9, 20. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9020020

AMA Style

Mouratidis D, Nikiforos MN, Kermanidis KL. Deep Learning for Fake News Detection in a Pairwise Textual Input Schema. Computation. 2021; 9(2):20. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9020020

Chicago/Turabian Style

Mouratidis, Despoina, Maria N. Nikiforos, and Katia L. Kermanidis 2021. "Deep Learning for Fake News Detection in a Pairwise Textual Input Schema" Computation 9, no. 2: 20. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9020020

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