Banca de QUALIFICAÇÃO: TUANY MARIAH LIMA DO NASCIMENTO

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : TUANY MARIAH LIMA DO NASCIMENTO
DATE: 09/07/2021
TIME: 09:00
LOCAL: Google Meets
TITLE:

Using semi-supervised models for fake news detection: a case study on Covid-19


KEY WORDS:

Fake News, Semi-Supervised Learning, COVID-19


PAGES: 40
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Matemática da Computação
SPECIALTY: Modelos Analíticos e de Simulação
SUMMARY:

Fake News has been a big problem for society for a long time. It has been magnified,reaching worldwide proportions, mainly with the growth of social networks and instantchat platforms where any user can quickly interact with news, either by sharing, throughlikes and retweets or presenting hers/his opinion on the topic. Since this is a very fastphenomenon, it became humanly impossible to manually identify and highlight any fakenews. Therefore, the search for automatic solutions for fake news identification, mainlyusing machine learning models, has grown a lot in recent times, due to the variety oftopics as well as the variety of fake news propagated. Most solutions focus on supervisedlearning models, however, in some datasets, there is an absence of labels for most of theinstances. For this, the literature presents the use of semi-supervised learning algorithmswhich are able to learn from a few labeled data. Thus, this work will investigate the use ofsemi-supervised learning models for the detection of fake news, using as a case study theoutbreak of the Sars-CoV-2 virus, the COVID-19 pandemic.


BANKING MEMBERS:
Presidente - 2524467 - MARJORY CRISTIANY DA COSTA ABREU
Externo ao Programa - 1669545 - DANIEL SABINO AMORIM DE ARAUJO
Externa ao Programa - 2938129 - LAURA EMMANUELLA ALVES DOS SANTOS SANTANA DE OLIVEIRA
Externa ao Programa - 1912232 - LIVIA CIRNE DE AZEVEDO PEREIRA
Notícia cadastrada em: 15/06/2021 15:33
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