<p>This study advances social network analysis (SNA) as an evaluative methodology for assessing the relational and semantic quality of emerging technology discourse, using Virtual Reality (VR) in retail as an empirical case. While prior research has largely focused on individual adoption and acceptance of VR technologies, less attention has been given to the quality of social discourse through which emerging technologies are collectively interpreted and circulated. Grounded in social capital theory, this study examines how structural and cognitive dimensions of social capital jointly characterize early-stage VR retail discourse. Using a four-year Twitter dataset comprising 11,145 accounts and 60,296 relational ties, this study develops a network-based framework to evaluate diffusion capacity in VR retail discourse. Structural relational quality is assessed through centrality-based indicators capturing brokerage, visibility, and interaction intensity, while semantic quality is examined through patterns of semantic coherence aligned with dimensions of cognitive absorption. The results reveal a highly modular yet connected network in which thematically segmented conversational clusters remain linked through bridging actors, alongside stable semantic patterns reflecting focused immersion, curiosity, and heightened enjoyment. Theoretically, this study extends social capital research by demonstrating how structural and cognitive resources embedded in networked discourse can be empirically evaluated using SNA-derived quality proxies. Methodologically, it advances SNA beyond descriptive mapping by positioning network metrics as evaluative indicators of diffusion capacity in the early phase of technology discourse. Practically, the findings offer retailers and technology stakeholders a framework for assessing innovation readiness and designing digital engagement strategies in emerging technology environments.</p>