BACKGROUND
During the period surrounding the approval and initial distribution of Pfizer-BioNTech’s COVID-19 vaccine, many users took to social media to voice their opinions on the vaccine. They formed pro- and anti-vaccination groups and influenced behaviors to vaccinate or not to vaccinate. The methods of persuasion and manipulation for convincing audiences online can be characterized under a framework for social-cyber maneuvers known as the BEND maneuvers. Previous studies have been conducted on the spread of COVID-19 vaccine disinformation. However, none have used a process that conducts comparative analyses over time on both community stances and the competing techniques of manipulating both the narrative and network structure to persuade target audiences.
OBJECTIVE
This study aimed to understand community response to vaccination by dividing Twitter data from the initial Pfizer-BioNTech COVID-19 vaccine rollout into pro-vaccine and anti-vaccine stances, identifying key actors and groups, and evaluating how the different communities use social-cyber maneuvers, or BEND maneuvers, to influence their target audiences and the network as a whole.
METHODS
COVID-19 Twitter vaccine data was collected using the Twitter API for one-week periods before, during, and six weeks after the initial Pfizer-BioNTech rollout (December 2020-January 2021). Bot identifications and linguistic cues were derived for users and tweets, respectively, to use as metrics for evaluating social-cyber maneuvers. ORA-PRO software was then used to separate the vaccine data into pro-vaccine and anti-vaccine communities and facilitate identifying key actors, groups, and BEND maneuvers for a comparative analysis between each community and the entire network.
RESULTS
Both the pro-vaccine and anti-vaccine communities used combinations of the 16 BEND maneuvers to persuade their target audiences of their particular stances. Our analysis showed how each side attempted to build its own community while simultaneously narrowing and neglecting the opposing community. Pro-vaccine users primarily used positive maneuvers such as excite and explain messages to encourage vaccination and backed leaders within their group. In contrast, anti-vaccine users relied on negative maneuvers to dismay and distort messages with narratives on side effects and death and attempted to neutralize the effectiveness of the leaders within the pro-vaccine community. Furthermore, nuking through platform policies showed to be effective in reducing the size of the anti-vaccine online community and the quantity of anti-vaccine messages.
CONCLUSIONS
Social media continues to be a domain for manipulating beliefs and ideas. These conversations can ultimately lead to real-world actions such as to vaccinate or not to vaccinate against COVID-19. Moreover, social media policies should be further explored as an effective means for curbing disinformation and misinformation online.
CLINICALTRIAL
Not applicable
Comparative analysis of contextual and context-free embeddings in disaster prediction from Twitter data