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Mapping of Subjective Accounts into Interpreted Clusters (MOSAIC): Topic Modelling and LLM applied to Stroboscopic Phenomenology.

Neurosci Conscious April 7, 2026 Peer reviewed DOI: 10.1093/nc/niag008 via PubMed Central

Summary

This work presents MOSAIC, a method that combines topic modeling with large language models to analyze subjective, first-person accounts of stroboscopic experiences. By mapping these descriptions into interpreted clusters, the approach aims to systematically organize and understand the structure of stroboscopic phenomenology, offering a computational tool for qualitative research in consciousness studies.

Study at a glance

Design theoretical or methodological paper
Key finding MOSAIC effectively integrates topic modeling and large language models to cluster and interpret subjective reports of stroboscopic experiences.

Abstract

Mapping of Subjective Accounts into Interpreted Clusters (MOSAIC): Topic Modelling and LLM applied to Stroboscopic Phenomenology.

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