The use of Data Augmentation as a technique for improving neural network
accuracy in detecting fake news about COVID-19
- URL: http://arxiv.org/abs/2205.00452v1
- Date: Sun, 1 May 2022 11:52:53 GMT
- Title: The use of Data Augmentation as a technique for improving neural network
accuracy in detecting fake news about COVID-19
- Authors: Wilton O. J\'unior, Mauricio S. da Cruz, Andre Brasil Vieira
Wyzykowski, Arnaldo Bispo de Jesus
- Abstract summary: This paper aims to present how the application of Natural Language Processing (NLP) and data augmentation techniques can improve the performance of a neural network for better detection of fake news in the Portuguese language.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper aims to present how the application of Natural Language Processing
(NLP) and data augmentation techniques can improve the performance of a neural
network for better detection of fake news in the Portuguese language. Fake news
is one of the main controversies during the growth of the internet in the last
decade. Verifying what is fact and what is false has proven to be a difficult
task, while the dissemination of false news is much faster, which leads to the
need for the creation of tools that, automated, assist in the process of
verification of what is fact and what is false. In order to bring a solution,
an experiment was developed with neural network using news, real and fake,
which were never seen by artificial intelligence (AI). There was a significant
performance in the news classification after the application of the mentioned
techniques.
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