Virtual lab coats: The effects of verified source information on social media post credibility

Author:

Geels JorritORCID,Graßl PaulORCID,Schraffenberger HannaORCID,Tanis Martin,Kleemans Mariska

Abstract

Social media platform’s lack of control over its content made way to the fundamental problem of misinformation. As users struggle with determining the truth, social media platforms should strive to empower users to make more accurate credibility judgements. A good starting point is a more accurate perception of the credibility of the message’s source. Two pre-registered online experiments (N = 525;N = 590) were conducted to investigate how verified source information affects perceptions of Tweets (study 1) and generic social media posts (study 2). In both studies, participants reviewed posts by an unknown author and rated source and message credibility, as well as likelihood of sharing. Posts varied by the information provided about the account holder: (1) none, (2) the popular method of verified source identity, or (3) verified credential of the account holder (e.g., employer, role), a novel approach. The credential was either relevant to the content of the post or not. Study 1 presented the credential as a badge, whereas study 2 included the credential as both a badge and a signature. During an initial intuitive response, the effects of these cues were generally unpredictable. Yet, after explanation how to interpret the different source cues, two prevalent reasoning errors surfaced. First, participants conflated source authenticity and message credibility. Second, messages from sources with a verified credential were perceived as more credible, regardless of whether this credential was context relevant (i.e., virtual lab coat effect). These reasoning errors are particularly concerning in the context of misinformation. In sum, credential verification as tested in this paper seems ineffective in empowering users to make more accurate credibility judgements. Yet, future research could investigate alternative implementations of this promising technology.

Publisher

Public Library of Science (PLoS)

Reference110 articles.

1. Belanger A. Twitter quietly drops $8 paid verification; “tricking people not ok,” Musk says; 2022. Available from: https://arstechnica.com/tech-policy/2022/11/twitter-quietly-drops-8-paid-verification-tricking-people-not-ok-musk-says/.

2. van Gastel B, Vervoort L, Bor D, Schraffenberger H, Jacobs B. Twid: Fighting Desinformation on Twitter with Authenticity; 2021. Available from: https://ihub.ru.nl/project/twid.page.

3. Conspiracy theories as stigmatized knowledge;M Barkun;Diogenes,2015

4. Social Media and Fake News in the 2016 Election;H Allcott;Journal of Economic Perspectives,2017

5. Riding the waves of “Web 2.0”;M Madden;Pew internet and American life project,2006

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