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Towards a soft three-level voting model (Soft T-LVM) for fake news detection.
- Source :
-
Journal of intelligent information systems [J Intell Inf Syst] 2022 Dec 23, pp. 1-21. Date of Electronic Publication: 2022 Dec 23. - Publication Year :
- 2022
- Publisher :
- Ahead of Print
-
Abstract
- Fake news has a worldwide impact and the potential to change political scenarios and human behavior, especially in a critical time like the COVID-19 pandemic. This work suggests a Soft Three-Level Voting Model (Soft T-LVM) for automatically classifying COVID-19 fake news. We train different individual machine learning algorithms and different ensemble methods in order to overcome the weakness of individual models. This novel model is based on the soft-voting technique to calculate the class with the majority of votes and to choose the classifiers to merge and apply at every level. We use the Grid search method to tune the hyper-parameters during the process of classification and voting. The experimental evaluation confirms that our proposed model approach has superior performance compared to the other classifiers.<br /> (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)
Details
- Language :
- English
- ISSN :
- 0925-9902
- Database :
- MEDLINE
- Journal :
- Journal of intelligent information systems
- Publication Type :
- Periodical
- Accession number :
- 36575748
- Full Text :
- https://doi.org/10.1007/s10844-022-00769-7