Fake news, desinformação e infodemia nas redes sociais: uma proposta de caracterização

• Ano de defesa: 2023
• Autor(a) principal: Abreu, Rosamelia Girão
• Orientador(a): Brito, Eliane Pereira Zamith
• Tipo de documento: Tese
• Tipo de acesso: Acesso embargado
• Idioma: por
• Palavras-chave em Português: Desinformação; Infodemia; Redes sociais; Notícias falsas; Antivacina
• Palavras-chave em Inglês: Disinformation; Fake news; Infodemic; Social media; False news; Antivaccine; COVID-19
• Link de acesso: https://hdl.handle.net/10438/34721

In recent years, we have seen enormous concern about the spread of fake news on social media, with potential major political and social consequences, because it spreads faster, deeper and wider than factual information. In social networks, echo chambers, algorithms and cognitive biases play an important role in shaping the behavior of their users. However, the very definition of fake news is still the subject of intense debate and the framework of available research is still recent and inconclusive, which demands greater examination of this subject. In fact, despite the growth of studies focused on fake news, researchers of this phenomenon have not yet reached a single definition for the concept. Above all, although some allegations can be verified in a fact check process and then filtered if they are false, the fact is that many techniques can be used to propagate lies on social networks without making, stricto sensu, false allegations. Most authors who have looked at the topic have started from the principle that truth and falsehood can be concretely defined. How can we really know what is true? Or rather, what is the truth? Thus, as a theoretical contribution, this work brings more clarity to the definition of the fake news construct, proposing an alternative criterion for its classification. This work is therefore located at the intersection of Marketing studies on Social Networks and the formation of public opinion in Communication. Social constructivism was adopted as a philosophical perspective, with a qualitative research strategy. Data collected on Twitter (currently called Platform X) was used in this research, from March 2020 to February 2021, during the COVID-19 pandemic and included, monthly, the 30 largest posts circulated on Twitter regarding the topic “vaccine”, in a total of 360 tweets, which were subsequently analyzed using the Content Analysis technique. The study offers a classification for fake news based on three vectors: the graphic format, the intention to cause damage and factuality or clear and present danger, in addition to suggesting clear criteria for the practical application of this classification. This study contributes to those formulating communication strategies, especially in times of crisis.