Unraveling the use of disinformation hashtags by social bots during the COVID-19 pandemic: social networks analysis
Metadatos
Mostrar el registro completo del ítemAutor
Suarez Lledo, Victor; Ortega Martin, Esther; Carretero-Bravo, Jesús; Ramos-Fiol, Begoña; Alvarez Galvez, JavierEditorial
JMIR
Materia
social media misinformation COVID-19
Fecha
2025-01-09Referencia bibliográfica
Suarez-Lledo V, Ortega-Martin E, Carretero-Bravo J, Ramos-Fiol B, Alvarez-Galvez J Unraveling the Use of Disinformation Hashtags by Social Bots During the COVID-19 Pandemic: Social Networks Analysis JMIR Infodemiology 2025;5:e50021 URL: https://infodemiology.jmir.org/2025/1/e50021 doi: 10.2196/50021
Resumen
Background: During the COVID-19 pandemic, social media platforms have been a venue for the exchange of messages,
including those related to fake news. There are also accounts programmed to disseminate and amplify specific messages, which
can affect individual decision-making and present new challenges for public health.
Objective: This study aimed to analyze how social bots use hashtags compared to human users on topics related to misinformation
during the outbreak of the COVID-19 pandemic.
Methods: We selected posts on specific topics related to infodemics such as vaccines, hydroxychloroquine, military, conspiracy,
laboratory, Bill Gates, 5G, and UV. We built a network based on the co-occurrence of hashtags and classified the posts based on
their source. Using network analysis and community detection algorithms, we identified hashtags that tend to appear together in
messages. For each topic, we extracted the most relevant subtopic communities, which are groups of interconnected hashtags.
Results: The distribution of bots and nonbots in each of these communities was uneven, with some sets of hashtags being more
common among accounts classified as bots or nonbots. Hashtags related to the Trump and QAnon social movements were common
among bots, and specific hashtags with anti-Asian sentiments were also identified. In the subcommunities most populated by
bots in the case of vaccines, the group of hashtags including #billgates, #pandemic, and #china was among the most common.
Conclusions: The use of certain hashtags varies depending on the source, and some hashtags are used for different purposes.
Understanding these patterns may help address the spread of health misinformation on social media networks.