Text mining and sentiment analysis applied to Twitter posts about Covid-19 vaccines

• Autor(a) principal: Farias, Franciele Leal
• Data de Publicação: 2022
• Outros Autores: Oliveira , Lorena Sophia Campos de
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/35490
• topic: Pandemia; Vacuna; Covid-19; Extracción de textos; Análisis de los sentimientos.; Pandemic; Vaccine; Covid-19; Text mining; Sentiment analysis.; Pandemia; Covid-19; Vacina; Mineração de textos; Análise de sentimentos.

The Covid-19 pandemic is already considered by many scholars to be the biggest health problem of the 21st century and claiming the lives of thousands of people. The speed with the disease spread and changed the lives of the world's population generated a lot of emotions and feelings in people. Since the discovery of the new coronavirus, a race began to develop a vaccine that would be effective to combat the disease, growing the population's desire for its arrival. The work analyzes the feelings that the Brazilian population has developed in relation to vaccines created to combat Covid-19, through the use of sentiment analysis and data mining techniques. The construction of the database took place through the capture of public posts made available by the Twitter API. The algorithm developed during the research is based on the Python programming language and implemented on the Jupyter Notebook platform. The sentiment analysis process was carried out through semantic analysis, using the lexicon dictionary for the Portuguese language SentiLex-PT.