# The use of Data Augmentation as a technique for improving neural network accuracy in detecting fake news about COVID-19

arXiv: https://arxiv.org/abs/2205.00452 · HTML: https://mlsanity.com/paper/2205.00452/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 21 references that are in the map.
- First posted on arXiv 1 May 2022.

## Builds on (most cited first, 6 of 6)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Fighting an Infodemic: COVID-19 Fake News Dataset](https://mlsanity.com/paper/2011.03327/) (2020)
- [Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection](https://mlsanity.com/paper/2102.08924/) (2021)
- [Challenges in Combating COVID-19 Infodemic -- Data, Tools, and Ethics](https://mlsanity.com/paper/2005.13691/) (2020)
- [TUDublin team at Constraint@AAAI2021 -- COVID19 Fake News Detection](https://mlsanity.com/paper/2101.05701/) (2021)
- [Fake News Detection: a comparison between available Deep Learning techniques in vector space](https://mlsanity.com/paper/2102.09470/) (2021)

## Built on by (most cited first, 3 of 3)

- [Data Augmentation for Fake Reviews Detection in Multiple Languages and Multiple Domains](https://mlsanity.com/paper/2504.06917/) (2025)
- [Addressing Data Scarcity in Bangla Fake News Detection: An LLM-Based Dataset Augmentation Approach](https://mlsanity.com/paper/2605.01292/) (2026)
- [Evaluation Metrics for Text Data Augmentation in NLP](https://mlsanity.com/paper/2402.06766/) (2024)

## Abstract (arXiv)

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.