The Evolutionary Path of Calligraphy Elements in the Field of Visual Design: A CiteSpace-Based Knowledge Mapping Analysis

This study focuses on the cross-media application of calligraphy elements in visual design, encompassing print, digital, and interactive media.Addressing the limitations of previous researchprimarily centered on individual case studies and lacking a systematic evolutionary path-this paper employs the bibliometric visualization tool CiteSpace to analyze 245 core articles published between 2004 and 2025 in the Web of Science database.The dataset encompasses 215 journals, 716 authors, 456 institutions, and 66 countries or regions.Methodologically, the study integrates keyword cooccurrence analysis, burst term detection, and Log-Likelihood Ratio (LLR) clustering to construct a knowledge map that reveals the developmental trajectory and thematic shifts of the field.The results identify four key stages: (1) the technological exploration phase (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011), featuring terms such as "virtual hairy brush" and "modeling"; (2) the design practice phase (2012-2016), focusing on "graphic design"; (3) the cross-cultural comparison phase (2015-2020), marked by "Arabic calligraphy"; and (4) the intelligence and fusion phase (2018-2024), characterized by emergent terms like "deep learning" and "feature fusion"-with "deep learning" exhibiting the highest burst strength of 2.15.In terms of national contributions, Chinese scholars account for nearly 50% of the publications, demonstrating significant academic leadership in the field.This study is the first to construct a macrolevel knowledge map of the "calligraphy elements + visual design" domain, providing data-driven insights into the evolving logic of calligraphy in contemporary visual expression.It also offers theoretical and methodological references for cross-media design practices that incorporate artificial intelligence, mixed reality, and cultural sustainability.However, the study relies solely on the Web of Science database, which may overlook regional or non-English literature, and the CiteSpace clustering algorithm has limited ability to interpret soft factors such as cultural context.Future research should incorporate qualitative methods to complement these limitations.