Revealing complexities when adult readers engage in the credibility evaluation of social media posts

19 citations

Abstract

The internet, including social networking sites, has become a major source of health information for laypersons. Yet, the internet has also become a platform for spreading misinformation that challenges adults' ability to critically evaluate the credibility of health messages. To better understand the factors affecting credibility judgements, the present study investigates the role of source characteristics, evidence quality, crowdsourcing platform, and prior beliefs of the topic in adult readers' credibility evaluations of short health-related social media posts. Researchers designed content for the posts concerning five health topics by manipulating source characteristics (source's expertise, gender, and ethnicity), accuracy of the claims, and evidence quality (research evidence, testimony, consensus, and personal experience) in the posts. Then, accurate and inaccurate posts varying in these other manipulated aspects were computer-generated. Crowdworkers (N = 844) recruited from two platforms were asked to evaluate the credibility of ten social media posts, resulting in 8380 evaluations. Before credibility evaluation, participants' prior beliefs on the topics of the posts were assessed. Results showed that prior belief consistency and source expertise most affected the perceived credibility of accurate and inaccurate social media posts after controlling for the topic of the post. In contrast, the quality of evidence supporting the health claim mattered relatively little. In addition, the data collection platform had a notable impact, such that posts containing inaccurate claims were much more likely to be rated higher on one platform compared to the other. Implications for credibility evaluation theory and research are discussed.

19
Citations
Research
Paper Only

Study specs

Researchers created social media posts with manipulated source characteristics, claim accuracy, and evidence quality. Participants evaluated the credibility of these posts via crowdsourcing platforms after having their prior topic beliefs assessed.

Sample Size
N=844
Study Type
Experimental Study
Year
2024
Human Data Platform
Prolific

Measured Outcomes

The perceived credibility of health-related social media posts based on source characteristics, evidence quality, prior beliefs, and the platform used for data collection.

Peer Review & Critical Discussion

3 threads

Potential Selection Bias in 2023 Cohort

DSJDr. Sarah J.
Verified PhD Candidate
12 replies

The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.

2 hours ago

Non-naive Participants Issue

MCM. Chen (OpenAI)
Data Scientist
8 replies

I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.

5 hours ago

RLHF Applicability to This Study Design

PRWProf. R. Williams
Verified Researcher
15 replies

The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.

1 day ago

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