Social media virality metrics as interpretive cues: Affective pathways to sharing conflicting health information

Virality metrics—such as the number of likes, shares, and comments—are often conceptualized in digital media research as heuristic or normative cues that help individuals assess credibility, popularity, or social approval. This study proposes instead that virality metrics function as interpretive cues that shape how users emotionally and cognitively engage with conflicting health information on social media. These metrics may influence how people perceive social disagreement, ambiguity, or controversy rather than merely signaling popularity. To examine this idea, an online experiment ( N = 876) exposed participants to mock blog posts containing contradictory health claims—about either artificial sweeteners or processed meat—paired with either high or low virality metrics. The results supported a serial mediation model: virality metrics affected sharing intention by increasing perceived controversy, which in turn heightened anxiety and led to greater motivation to share the post. These findings challenge traditional heuristic and normative frameworks, instead positioning virality metrics as emotionally charged and interpretively meaningful cues that influence how users make sense of ambiguous information. The present study contributes to a more psychologically nuanced understanding of digital behavior in complex informational environments. It also raises practical considerations for platform design and health communication, where visible metrics may inadvertently amplify uncertainty, emotional discomfort, and the spread of controversial or ambiguous content—even in the absence of clear credibility cues. • Virality metrics act as interpretive cues, not merely as heuristic indicators. • Virality metrics shape both emotional and cognitive processing of health messages. • The study proposes and tests a novel serial mediation model through an online experiment. • High virality increases perceived controversy in conflicting health information. • Perceived controversy evokes anxiety, which, in turn, drives the intention to share posts.

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Publication Details

Journal
Computers in Human Behavior Reports
Published
2025-12-02
DOI
https://doi.org/10.1016/j.chbr.2025.100893
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
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article

Social media virality metrics as interpretive cues: Affective pathways to sharing conflicting health information

Kilhoe Na
Computers in Human Behavior Reports
Misinformation and Its Impacts
article

Social media virality metrics as interpretive cues: Affective pathways to sharing conflicting health information

Kilhoe Na
article en

Abstract

Virality metrics—such as the number of likes, shares, and comments—are often conceptualized in digital media research as heuristic or normative cues that help individuals assess credibility, popularity, or social approval. This study proposes instead that virality metrics function as interpretive cues that shape how users emotionally and cognitively engage with conflicting health information on social media. These metrics may influence how people perceive social disagreement, ambiguity, or controversy rather than merely signaling popularity. To examine this idea, an online experiment ( N = 876) exposed participants to mock blog posts containing contradictory health claims—about either artificial sweeteners or processed meat—paired with either high or low virality metrics. The results supported a serial mediation model: virality metrics affected sharing intention by increasing perceived controversy, which in turn heightened anxiety and led to greater motivation to share the post. These findings challenge traditional heuristic and normative frameworks, instead positioning virality metrics as emotionally charged and interpretively meaningful cues that influence how users make sense of ambiguous information. The present study contributes to a more psychologically nuanced understanding of digital behavior in complex informational environments. It also raises practical considerations for platform design and health communication, where visible metrics may inadvertently amplify uncertainty, emotional discomfort, and the spread of controversial or ambiguous content—even in the absence of clear credibility cues. • Virality metrics act as interpretive cues, not merely as heuristic indicators. • Virality metrics shape both emotional and cognitive processing of health messages. • The study proposes and tests a novel serial mediation model through an online experiment. • High virality increases perceived controversy in conflicting health information. • Perceived controversy evokes anxiety, which, in turn, drives the intention to share posts.

Computers in Human Behavior ReportsVol. 21
Merrimack College (US)
Openalex Percentile: Top 53%
Misinformation and Its Impacts
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