Real Talk, Virtual Faces: Symbolic-Semantic Discourse Geometry of Virtual and Human Influencer Audiences
Shahram Chaudhry, Sidahmed Benabderrahmane, Talal Rahwan

TL;DR
This study introduces a symbolic-semantic framework to analyze and compare audience discourse patterns around virtual and human influencers on social media, revealing distinct organizational and sentiment differences.
Contribution
It develops a novel framework combining Formal Concept Analysis and semantic embedding to analyze discourse structure and sentiment in large-scale social media comments.
Findings
HI discourse is stability-centered with positive sentiment linked to low neuroticism.
VI discourse exhibits multiple regimes and more dispersed semantic concepts.
VI comments show more negative sentiment in sensitive topics like mental health and body image.
Abstract
Virtual influencers~(VIs) -- digitally constructed social-media personas -- are becoming increasingly visible in online culture, marketing, and identity formation. Yet it remains unclear whether audiences respond to them through the same discourse patterns used for human influencers~(HIs), or whether virtuality produces distinctive modes of reaction. Existing studies often rely on surveys, engagement statistics, or marginal sentiment distributions, which reveal what audiences say but not how affective, topical, and psycholinguistic signals are jointly organised. We introduce a symbolic-semantic framework for analysing audience discourse around virtual and human influencers. The symbolic layer uses Formal Concept Analysis and association rule mining to extract closed co-occurrence structures from sentiment labels, topic tags, and Big Five psycholinguistic cues. The semantic layer…
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