O uso de data augmentation como técnica para o aprimoramento de redes neurais a fim de detectar notícias falsas sobre a COVID-19
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Date
2021-06-11
Journal Title
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Publisher
Universidade Católica do Salvador
Abstract
This paper aims to present how the application of Natural Lan-
guage 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.
Description
Keywords
Redes neurais, Notícia falsa, COVID-19, Fake news, Data augmentation