Author(s)

Qing Miao

Affiliation(s)

School of Art, Anhui University of Finance and Economics, Bengbu 233030, Anhui, China.

Corresponding Author

Qing Miao

ABSTRACT

This study employs knowledge graph visualization analysis to conduct scientometric and comparative analysis of academic literature on textile and embroidery art research from 2004 to 2024. Differing from traditional literature reviews that are limited by subjective judgments, the research utilizes computer science data analysis tools to present the knowledge structure, core themes, and cutting-edge trends in textile and embroidery art research, while proactively identifying deeper research gaps and interdisciplinary intersections. Macroscopically, the CiteSpace data analysis software is employed to examine the diachronic spatial dimensions of textile and embroidery art research development. Microscopically, the LDA topic model is applied to the literature dataset for data modeling, exploring implicit thematic structures within the dataset. This study provides objective and quantifiable empirical evidence for future research in textile and embroidery art, promoting the integration of traditional humanistic speculation with scientific data computation in academic research, and offering methodological references for other art and humanities disciplines.

KEYWORDS

Weaving and embroidery art; Visual analysis; LDA topic model; Topic evolution

CITE THIS PAPER

Qing Miao. Visual analysis of research on weaving and embroidery art based on knowledge map. Trends in Social Sciences and Humanities Research. 2026, 4(1): 1-16. DOI: https://doi.org/10.61784/tsshr3205.

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