Neutrosophic technarrative architecture for symbolic–emotional evaluation of virtual architectural spaces in VR

Virtual reality (VR) is increasingly employed to investigate human-environment interactions; however, current evaluation methods remain fragmented. Physical–functional metrics, biofeedback signals, and self-report data are frequently analyzed in isolation, leaving the symbolic–narrative dimension of architecture largely implicit. This Hypothesis and Theory article introduces the Neutrosophic Technarrative Architecture (NTA): a robust methodological framework and computational pipeline for the symbolic–emotional evaluation of virtual architectural spaces. The proposed framework integrates four core components: (1) the Neutrosophic Technarrative Model (NTM), which encodes architectural spaces through symbolic nodes such as justice, identity, hope, resistance, and eco-symbiosis; (2) immersive VR scenarios acting as controlled symbolic environments; (3) psychophysiological measures (EEG, GSR, HRV) as indicators of affective engagement; and (4) an AI-ready computational model that links symbolic design variables, biofeedback features, and user evaluations via neutrosophic inference. Rather than introducing new sensing technologies, the novelty of NTA lies in the symbolic–computational integration of existing VR and affective computing methods. We define the conceptual structure of NTA, formulate testable hypotheses, and provide a reproducible methodological blueprint—supported by open-source Python implementations—for multimodal analysis. We demonstrate that NTA (a) offers a systematic pipeline for connecting symbolic design intentions with measurable VR experiences, (b) employs neutrosophic representation to quantify ambiguity and indeterminacy in user responses, and (c) enables predictive modelling that transcends traditional self-report-only approaches. This work establishes a foundational research agenda at the intersection of VR user experience, neuroarchitecture, and ethically oriented design.