|Appears in Collections:||Management, Work and Organisation Journal Articles|
|Peer Review Status:||Refereed|
|Title:||COVID-19 and the "Film Your Hospital" Conspiracy Theory: Social Network Analysis of Twitter Data|
López Seguí, Francesc
Katz, Matthew S
social network analysis
|Citation:||Ahmed W, López Seguí F, Vidal-Alaball J & Katz MS (2020) COVID-19 and the “Film Your Hospital” Conspiracy Theory: Social Network Analysis of Twitter Data. Journal of Medical Internet Research, 22 (10), Art. No.: e22374. https://doi.org/10.2196/22374|
|Abstract:||Background: During the COVID-19 pandemic, a number of conspiracy theories have emerged. A popular theory posits that the pandemic is a hoax and suggests that certain hospitals are “empty.” Research has shown that accepting conspiracy theories increases the likelihood that an individual may ignore government advice about social distancing and other public health interventions. Due to the possibility of a second wave and future pandemics, it is important to gain an understanding of the drivers of misinformation and strategies to mitigate it. Objective: This study set out to evaluate the #FilmYourHospital conspiracy theory on Twitter, attempting to understand the drivers behind it. More specifically, the objectives were to determine which online sources of information were used as evidence to support the theory, the ratio of automated to organic accounts in the network, and what lessons can be learned to mitigate the spread of such a conspiracy theory in the future. Methods: Twitter data related to the #FilmYourHospital hashtag were retrieved and analyzed using social network analysis across a 7-day period from April 13-20, 2020. The data set consisted of 22,785 tweets and 11,333 Twitter users. The Botometer tool was used to identify accounts with a higher probability of being bots. Results: The most important drivers of the conspiracy theory are ordinary citizens; one of the most influential accounts is a Brexit supporter. We found that YouTube was the information source most linked to by users. The most retweeted post belonged to a verified Twitter user, indicating that the user may have had more influence on the platform. There was a small number of automated accounts (bots) and deleted accounts within the network. Conclusions: Hashtags using and sharing conspiracy theories can be targeted in an effort to delegitimize content containing misinformation. Social media organizations need to bolster their efforts to label or remove content that contains misinformation. Public health authorities could enlist the assistance of influencers in spreading antinarrative content.|
|Rights:||©Wasim Ahmed, Francesc López Seguí, Josep Vidal-Alaball, Matthew S Katz. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.10.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.|
|COVID-19 and the Film Your Hospital Conspiracy Theory Social Network Analysis of Twitter Data.pdf||Fulltext - Published Version||1.24 MB||Adobe PDF||View/Open|
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