論文
Distributional Concept Analysis of “Explain”: From Distant Reading to Cosmic Reading
2026 年 33 巻 p. 73-89
詳細
2026 年 33 巻 p. 73-89
Understanding how the verb explain functions across natural language is crucial for philosophy of explanation, corpus linguistics, and science and technology studies, yet existing approaches have lacked a comprehensive, distributional account of explanatory practices at scale. This study proposes Distributional Concept Analysis (DCA), a multilayered framework that integrates E5 sentence embeddings, UMAP-based semantic galaxy visualization, PCA-derived semantic axes, the Combined Topic Model (CTM), and GPT-5-assisted topic labeling. Using 10,000 instances of explain drawn from the British National Corpus, DCA constructs a high-dimensional “semantic galaxy” in which explanatory uses form distinct but interconnected star-like clusters corresponding to scientific, institutional, interactional, and narrative contexts. PCA reveals two continuous semantic axes-one ranging between scientific and narrative, and the other between institutional and interpersonal-that organize this galaxy globally, providing a distributed structure that extends beyond genre boundaries. CTM and GPT-5 further identify six coherent explanatory constellations, each defined by distinctive lexical, grammatical, and discourse features, which together demonstrate that explain serves as a hub linking diverse explanatory modes. These findings show that explanation is not a monolithic linguistic or conceptual category but a multi-centered semantic ecology shaped by genre, discourse aims, and interactional conditions. Conceptually, the study extends Moretti’s notion of distant reading by introducing cosmic reading, an approach that observes not only textual patterns but the semantic landscapes and constellations emergent from large-scale embeddings. By integrating quantitative semantics with generative interpretation, DCA operationalizes Machery’s call for empirical philosophy of science and broadens Overton’s corpus-based study of scientific explanation to encompass the full range of everyday explanatory practices. This work thus provides a new methodological foundation for analyzing explanation as a distributed, ecologically structured phenomenon in natural language.
