CA-Hashtags semantic networks: a metric study model of health information on social media

• Autor(a) principal: Andrade, Júlia Carvalho
• Data de Publicação: 2022
• Outros Autores: Cunha, Francisco José Aragão Pedroza, Magris, Patrícia Nicolau, Grilo, Marcos, Pereira, Hernane Borges de Barros
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: RECIIS (Online)
• Texto Completo: https://www.reciis.icict.fiocruz.br/index.php/reciis/article/view/2385
• topic: Covid-19; Social media; Information retrieval models; Health information exchange; Semantic networks.; Covid-19; Redes sociales; Modelos de recuperación de información; Intercambio de información en salud; Redes semánticas.; Covid-19; Mídias sociais; Modelos de recuperação da informação; Troca de informação em saúde; Redes semânticas.

Social media are important channels for the dissemination of information on public health. The goal of this paper is to present a model of quantitative analysis of information from the hashtags with respect to covid-19 on Facebook, called CA-Hashtag semantic networks. This model consists of the methods of semantic network analysis and co-occurrence analysis. The metrics used from May 2020 to January 2021 were: hashtag’s frequency, degree and betweenness centralities and incidence-fidelity index; and study of islands. The themes identified have been: ‘Education in the pandemic’; ‘Work and pandemic’; ‘Science, health and pandemic’; ‘Social isolation in the pandemic’; and ‘Politics and pandemic’. Applying the proposed model, it has been possible to identify the most relevant themes about covid-19 for Facebook users.