Who is Perceived to be an Expert on COVID-19 Vaccines on Social Media?: Biomedical Credentials Confer Expertise, Even Among Vaccine-hesitant and Conservative Observers

Abstract

Who is perceived to be an expert on COVID-19 vaccination on social media? We conducted two experimental studies investigating how the presence of biomedical credentials on social media profiles impacts users’ perceived expertise. Participants (Experiment 1 N = 200; Experiment 2 N = 201) viewed a series of Twitter profiles that appeared with or without biomedical credentials and judged to what extent they believed each user was an expert on the topic of COVID-19 vaccination. We found that the presence of biomedical credentials consistently increased perceptions of expertise, including among unvaccinated, vaccine-hesitant, and conservative participants. This work supports existing observations that biomedical credentials may be leveraged by both pro- and anti-vaccine communities to increase perceived credibility and message reach, and counters the narrative that those with anti-vaccination attitudes do not recognize biomedical credentials as conferring expertise.

Perceived experts are prevalent and influential within an antivaccine community on Twitter

“…Users that indicated expertise in any part of their profile (names, description, or both) at any point in time were tagged as perceived experts based on experimental evidence that users with biomedical expertise signals in their profiles are perceived to have greater expertise on COVID-19 vaccines ( 31 ). Users who may be perceived as biomedical experts based on their name who clarify that they are not biomedical experts in their description (e.g.…”

“…name: Dr Henry Jekyll, description: PhD in 19th century literature) were still included as perceived experts because users viewing their tweets in the main feed display would not see the description and may assume that they have a medical doctorate or doctoral degree in a biomedical field (as observed in Ref. ( 31 )). This classification underscores the difference between perceived experts who may or may not intend to be seen as biomedical experts but are nevertheless viewed as such due to platform design and self-proclaimed experts who deliberately claim expertise.…”

“…Additional examples of perceived expert and perceived nonexpert profiles based on those observed in this coengagement network are provided in Ref. ( 31 ). One author tagged all accounts in the coengagement network and two authors tagged a sample of 500 accounts to assess interrater reliability.…”

“…Importantly, prestige-biased learning relies on signifiers of expertise that may or may not be accurate or correspond with actual competence in a given domain ( 25 , 30 ). Therefore, we will refer to perceived experts to denote individuals whose profiles contain signals that have been shown experimentally to increase the likelihood that an individual is viewed as an expert on COVID-19 vaccines ( 31 ), although credentials may be misrepresented or misunderstood (user profiles may be deceptive or ambiguous, audiences may not understand the domain specificity of expertise, and platform design may impair assessments of expertise if partial profile information is displayed alongside posts). We focus on the understudied role of perceived experts as potential antivaccine influencers who accrue influence through prestige bias ( 4 , 13 ).…”