SILVA, R. A. B.; http://lattes.cnpq.br/7433099166567604; SILVA, Rafaela de Amorim Barbosa.
Abstract:
Fake News are deliberately false or misleading information created and disseminated with the aim of
deceiving the public. These news articles are often designed to resemble legitimate news. Their
objective is to manipulate public opinion, spread misinformation, influence elections, generate
controversy, or to have financial gains. With the advent of social media, people have started
consuming news online as it is extremely simple, fast, and easily accessible. However, this has also led
to an increase in the dissemination of fake news. In recent years, we have seen that elections and
public opinion on important social issues have been influenced by the spread of fake news. They are
created and spread rapidly, highlighting the urgent need for rapid detection. In this work, we propose
a methodology for detecting fake news using deep neural networks, with a dataset of over 2 million
tweets from the Brazilian presidential elections of 2022, labeled automatically by a weak supervision
model, with F1-score of 98% on non-fake news tweets, and F1-score of 47% on tweets containing fake
news.