Content and Dynamics of Websites Shared Over Vaccine-Related Tweets in COVID-19 Conversations: Computational Analysis

Abstract

Background The onset of the COVID-19 pandemic and the consequent “infodemic” increased concerns about Twitter’s role in advancing antivaccination messages, even before a vaccine became available to the public. New computational methods allow for analysis of cross-platform use by tracking links to websites shared over Twitter, which, in turn, can uncover some of the content and dynamics of information sources and agenda-setting processes. Such understanding can advance theory and efforts to reduce misinformation. Objective Informed by agenda-setting theory, this study aimed to identify the content and temporal patterns of websites shared in vaccine-related tweets posted to COVID-19 conversations on Twitter between February and June 2020. Methods We used triangulation of data analysis methods. Data mining consisted of the screening of around 5 million tweets posted to COVID-19 conversations to identify tweets that related to vaccination and including links to websites shared within these tweets. We further analyzed the content the 20 most-shared external websites using a mixed methods approach. Results Of 841,896 vaccination-related tweets identified, 185,994 (22.1%) contained links to specific websites. A wide range of websites were shared, with the 20 most-tweeted websites constituting 14.5% (27,060/185,994) of the shared websites and typically being shared for only 2 to 3 days. Traditional media constituted the majority of these 20 websites, along with other social media and governmental sources. We identified markers of inauthentic propagation for some of these links. Conclusions The topic of vaccination was prevalent in tweets about COVID-19 early in the pandemic. Sharing websites was a common communication strategy, and its “bursty” pattern and inauthentic propagation strategies pose challenges for health promotion efforts. Future studies should consider cross-platform use in dissemination of health information and in counteracting misinformation.

Exploring Web-Based Twitter Conversations Surrounding National Healthcare Decisions Day and Advance Care Planning From a Sociocultural Perspective: Computational Mixed Methods Analysis

“…In addition, with the rise of TikTok during the COVID-19 pandemic [ 67 ], researchers should consider moving toward building a bridge that connects social media messages related to ACP across platforms and users alike. Finally, future studies may go beyond the text of tweets to examine external links [ 68 ], visual communication [ 69 ], and communication across different social media [ 70 ].…”

Cross-platform spread: vaccine-related content, sources, and conspiracy theories in YouTube videos shared in early Twitter COVID-19 conversations

“…The analysis reported here is part of a larger study that examined vaccination-related tweets. 69 The analyzed data were originally collected in two different studies that examined COVID-19 Twitter conversations in the early months of the pandemic. The first data set was based on a collection of tweet IDs gathered using general COVID-19 related keywords, such as “coronavirus” and “Wuhancoronavirus.” 70 We used “hydration,” a a process of gathering all the pertinent information about each tweet into the JavaScript Object Notation (JSON) format file 71 via the Twitter Search API b on all of the tweet IDs.…”

Cross-platform information spread during the January 6th capitol riots

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“…Recent research in the field has identified the use of external content like URLs (Horawalavithana et al 2021;Giglietto st al. 2020;Cruickshank et al 2021) and cross-platform behaviors Kin and Sameera 2021;Iamnitchi et al 2020) in the spread of mis/ disinformation.…”