Paolo Joshua R. Billones, Dailyne D. Macasaet, Shearyl U. Arenas
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Bilingual Fake News Detection Algorithm Using Naïve Bayes and Support Vector Machine Models
This study aims to mitigate the absorption of fraudulent news by exploring the feasibility of using Naive Bayes and SGD classifier models in predicting whether the English or Filipino article is real or fake. This is accomplished by training the models through large pre-processed datasets. After evaluation, both models have achieved an accuracy of 93% and 95% accuracy respectively.
IET NetworksCOMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
5.00
自引率
0.00%
发文量
41
审稿时长
33 weeks
期刊介绍:
IET Networks covers the fundamental developments and advancing methodologies to achieve higher performance, optimized and dependable future networks. IET Networks is particularly interested in new ideas and superior solutions to the known and arising technological development bottlenecks at all levels of networking such as topologies, protocols, routing, relaying and resource-allocation for more efficient and more reliable provision of network services. Topics include, but are not limited to: Network Architecture, Design and Planning, Network Protocol, Software, Analysis, Simulation and Experiment, Network Technologies, Applications and Services, Network Security, Operation and Management.