"Matched Linguistic Styles of Human\/Virtual Influencers Drive Social Media Sharing dataset"
收藏DataCite Commons2025-08-23 更新2026-05-03 收录
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https://ieee-dataport.org/documents/matched-linguistic-styles-humanvirtual-influencers-drive-social-media-sharing-dataset
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资源简介:
"Although linguistic styles shape social media engagement, the cognitive-affective pathways through which warmth- versus competence-oriented styles interact with sharer types (human\/virtual influencers) to influence tourist sharing lack empirical verification in video-based contexts. Through three experimental studies with cross-cultural tourist samples, we demonstrate: (1) Person perception asymmetry: Human influencers\u2019 warmth-oriented styles and virtual influencers\u2019 competence-oriented styles trigger synergistic effects on sharing intention; (2) Serial mediation mechanism: Processing fluency (cognitive) initiates a causal chain culminating in psychological richness (affective)\u2014providing initial evidence for this affective driver in sharing behaviors; (3) Contextual constraint: Temporal perception moderates this relationship, where queue management interventions (reducing perceived duration) boost sharing. We propose: a) Matched linguistic strategies: Warmth-oriented communication for human vs. competence-oriented for virtual influencers; b) Psychological richness priming through experiential narratives paired with temporal perception optimization. Theoretical contributions include: (i) Psychological richness as a personality-relevant affective mediator beyond satisfaction, (ii) Temporal perception as a socio-cognitive boundary condition, advancing person-agent interaction theory in digital environments."
提供机构:
IEEE DataPort
创建时间:
2025-08-23



