Open Access
ARTICLE
Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network
Dheeraj Kumar Dixit*, Amit Bhagat, Dharmendra Dangi
Department of Mathematics and Computer Applications, Maulana Azad National Institute of Technology (MANIT), Bhopal, Madhya Pradesh, India
* Corresponding Author: Dheeraj Kumar Dixit. Email:
(This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Computers, Materials & Continua 2022, 71(3), 5733-5750. https://doi.org/10.32604/cmc.2022.023628
Received 14 September 2021; Accepted 04 November 2021; Issue published 14 January 2022
Abstract
In recent years, social media platforms have gained immense popularity. As a result, there has been a tremendous increase in content on social media platforms. This content can be related to an individual's sentiments, thoughts, stories, advertisements, and news, among many other content types. With the recent increase in online content, the importance of identifying fake and real news has increased. Although, there is a lot of work present to detect fake news, a study on Fuzzy CRNN was not explored into this direction. In this work, a system is designed to classify fake and real news using fuzzy logic. The initial feature extraction process is done using a convolutional recurrent neural network (CRNN). After the extraction of features, word indexing is done with high dimensionality. Then, based on the indexing measures, the ranking process identifies whether news is fake or real. The fuzzy CRNN model is trained to yield outstanding results with 99.99 ± 0.01% accuracy. This work utilizes three different datasets (LIAR, LIAR-PLUS, and ISOT) to find the most accurate model.
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APA Style
Dixit, D.K., Bhagat, A., Dangi, D. (2022). Fake news classification using a fuzzy convolutional recurrent neural network. Computers, Materials & Continua, 71(3), 5733-5750. https://doi.org/10.32604/cmc.2022.023628
Vancouver Style
Dixit DK, Bhagat A, Dangi D. Fake news classification using a fuzzy convolutional recurrent neural network. Comput Mater Contin. 2022;71(3):5733-5750 https://doi.org/10.32604/cmc.2022.023628
IEEE Style
D.K. Dixit, A. Bhagat, and D. Dangi "Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network," Comput. Mater. Contin., vol. 71, no. 3, pp. 5733-5750. 2022. https://doi.org/10.32604/cmc.2022.023628