How dark triad language shapes credibility and helpfulness in online movie reviews?
Salman Yousaf, Keeyeon Ki-Cheon Park, Kyusung Hwang, Jong Min KimPurpose
This study aims to investigate how dark-triad-consistent linguistic markers in online movie reviews relate to credibility signals and perceived helpfulness within a digital customer-to-customer service encounter.
Design/methodology/approach
Using data from Naver.com, the authors examined platform credibility signaling and socially evaluative engagement (likes and dislikes) by performing textual content analysis of dark-triad-consistent linguistic markers at the review-text level using the Language Inquiry and Word Count method (Pennebaker et al., 2015). A follow-up experiment was performed on 240 participants, who were randomly assigned to one of four conditions in a 4 (Type of reviews: Neutral vs Psychopathy-framed vs Machiavellianism-framed vs Narcissism-framed) between-subjects design.
Findings
Reviews containing higher levels of narcissism-consistent and Machiavellianism-consistent linguistic markers were more likely to be classified as netizen-type (unverified) reviews on Naver, which functions as a platform-level credibility signal; the association for psychopathy-consistent markers was not statistically significant. Machiavellianism-consistent language was positively associated with both likes and dislikes, indicating polarized engagement. In the experiment, reviews framed with dark-triad-consistent language were rated as less authentic, less credible and less helpful than neutral reviews, and lower perceived authenticity mediated these effects.
Originality/value
By combining large-scale field data with an experiment, this study shows how dark-triad-consistent language functions as an observable review-text signal in a digital customer-to-customer service encounter that shapes platform classification, two-sided engagement (likes and dislikes) and reader judgments of authenticity, credibility and helpfulness. The authors treat dislikes as an unhelpfulness (disapproval) outcome (labeled “unusefulness” on the platform) that is not the inverse of helpfulness, because disapproval requires an affirmative negative evaluation and can co-occur with approval, thereby capturing approval–disapproval and polarization dynamics.