Idioma:

Twitter's Role in Combating the Magnetic Vaccine Conspiracy Theory: Social Network Analysis of Tweets

Ahmed, Wasim ; Das, Ronnie ; Vidal-Alaball, Josep ; Hardey, Mariann ; Fuster-Casanovas, Aïna

Journal of medical Internet research, 2023-03, Vol.25 (6), p.e43497-e43497 [Periódico revisado por pares]

Canada: Journal of Medical Internet Research

Texto completo disponível

Citações Citado por

Enviar para

Título:
Twitter's Role in Combating the Magnetic Vaccine Conspiracy Theory: Social Network Analysis of Tweets
Autor: Ahmed, Wasim ; Das, Ronnie ; Vidal-Alaball, Josep ; Hardey, Mariann ; Fuster-Casanovas, Aïna
Assuntos: Analysis ; Applications programming ; Athletes ; Broadcasting industry ; Cable television broadcasting industry ; Conspiracy ; Conspiracy theories ; COVID-19 ; COVID-19 vaccines ; Disinformation ; Epidemics ; Epidemiologists ; Health information ; Health promotion ; Health status ; Health surveillance ; Humans ; Immunization ; Influencer marketing ; Information management ; International economic relations ; Internet ; Magnetic Phenomena ; News ; Opinion leaders ; Original Paper ; Pandemics ; Popularity ; Public health ; Public opinion ; Social capital ; Social Media ; Social Network Analysis ; Social networks ; Social structure ; Sports ; Surveillance ; Uncertainty ; United States ; Vaccination ; Vaccines
É parte de: Journal of medical Internet research, 2023-03, Vol.25 (6), p.e43497-e43497
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: The popularity of the magnetic vaccine conspiracy theory and other conspiracy theories of a similar nature creates challenges to promoting vaccines and disseminating accurate health information. Health conspiracy theories are gaining in popularity. This study's objective was to evaluate the Twitter social media network related to the magnetic vaccine conspiracy theory and apply social capital theory to analyze the unique social structures of influential users. As a strategy for web-based public health surveillance, we conducted a social network analysis to identify the important opinion leaders sharing the conspiracy, the key websites, and the narratives. A total of 18,706 tweets were retrieved and analyzed by using social network analysis. Data were retrieved from June 1 to June 13, 2021, using the keyword vaccine magnetic. Tweets were retrieved via a dedicated Twitter application programming interface. More specifically, the Academic Track application programming interface was used, and the data were analyzed by using NodeXL Pro (Social Media Research Foundation) and Gephi. There were a total of 22,762 connections between Twitter users within the data set. This study found that the most influential user within the network consisted of a news account that was reporting on the magnetic vaccine conspiracy. There were also several other users that became influential, such as an epidemiologist, a health economist, and a retired sports athlete who exerted their social capital within the network. Our study found that influential users were effective broadcasters against the conspiracy, and their reach extended beyond their own networks of Twitter followers. We emphasize the need for trust in influential users with regard to health information, particularly in the context of the widespread social uncertainty resulting from the COVID-19 pandemic, when public sentiment on social media may be unpredictable. This study highlights the potential of influential users to disrupt information flows of conspiracy theories via their unique social capital.
Editor: Canada: Journal of Medical Internet Research
Idioma: Inglês

Links

View this record in MEDLINE/PubMed

Voltar para lista de resultados

Resultado 1 Avançar Ir para próxima página

Realização: Logos de Redes Sociais:

Twitter's Role in Combating the Magnetic Vaccine Conspiracy Theory: Social Network Analysis of Tweets

Ahmed, Wasim ; Das, Ronnie ; Vidal-Alaball, Josep ; Hardey, Mariann ; Fuster-Casanovas, Aïna

Canada: Journal of Medical Internet Research

Buscando em bases de dados remotas. Favor aguardar.