Quantifying the diffusion history of Yangmingism

The paper examines how Yangmingism, founded by Wang Shouren (Yangming), emerged as a response to challenges faced by Cheng-Zhu Neo-Confucianism in the mid-late Ming context (social unrest, evolving political economy, and changing views of agency). It spread rapidly through dialogues with other traditions (Zhuziology, Zen, Taoism), declined during the Qing, and revived in modern times with influence on political leaders and Neo-Confucian scholars, and internationally (e.g., Japan). The study argues that prior research has emphasized philosophical narratives and region-specific case studies focusing on disciples, lacking nationwide, quantitative, and spatial perspectives. Drawing on cultural diffusion theory and neo-cultural geography, the authors focus on acceptance (rather than mere knowledge) among Confucian scholars as the unit to quantify diffusion. They aim to map and model the spatio-temporal evolution, mechanisms, and patterns of Yangmingism diffusion across Ming–Qing China using social network analysis and GIS, thereby contributing quantitative insights to religious and cultural history.

Existing scholarship on Yangmingism is rich in philosophical and historical analysis, detailing doctrinal evolution and regional studies (e.g., works by Peng; studies by Suk, Jung, Ao, Qian). However, most prior studies focus on particular locales or on Wang Yangming’s direct disciples, often lacking a holistic spatial approach and overlooking broader acceptor networks. In the humanities, quantitative tools (social network analysis, GIS) have been increasingly used to study cultural diffusion and relational dynamics (e.g., Glomb, Fousek, McGillivray & Jenset). Cultural diffusion theory distinguishes between knowledge and acceptance, and neo-cultural geography emphasizes human agency in cultural processes. Recent digital humanities approaches analyze transmitters and acceptors to quantify diffusion. The paper situates Yangmingism’s spread within this literature, addressing gaps by integrating spatial-quantitative methods with historical sources to capture nationwide diffusion dynamics.

Study scope and period: 1508–1911 (from Wang Yangming’s Longchang Enlightenment to the end of the Qing). Diffusion is divided into five stages: rise (1508–1529), peak (1530–1579), decline (1580–1644), revival (1645–1705), and trough (1706–1911). Spatial scope includes administrative regions under Ming–Qing control. Data sources: Acceptors defined as Confucian scholars who accepted Yangmingism and produced related writings, drawn primarily from Ming Confucianism Case (Huang 2008), Qing Confucianism Case (Xu 2008), Chronology of Wang Yangming (Qian 2015), anthologies, local chronicles, and historical texts. Where records were sparse (e.g., North China, Guizhou), additional collections were consulted. Supporting information S1 contains the raw data. Acceptor identification: Criteria include (a) disciples listed in Wang Yangming’s Chronicle; (b) acceptance judgments in the Confucianism Cases; (c) explicit records in other collections showing endorsement/appreciation of Yangmingism. Scholars typically must have related writings; if not extant, historical records indicating acceptance are used. Accepted region determination: Based on zhou-level units. Using biographies, epitaphs, ritual chronologies, local chronicles, and timelines of lectures and study, the authors matched communicators and recipients in time-space, considering teacher-student, familial, and friendship ties. ArcGIS was used to geolocate events. Diffusion type classification: For acceptor-mediated diffusion, if the nth and (n+1)th generation accept in the same region, it is expansion diffusion; if different regions, relocation diffusion. Diffusion via writings to regions without prior acceptors is treated as relocation diffusion. Measures: Acceptance A(nj) = E(nj) + Ci(nj); Dissemination D(nj) = E(nj) + Co(nj). Degree centrality of relocation diffusion computed via out-degree Co(nj) = Σ xjk and in-degree Ci(nj) = Σ xkj across connected regions. Analytical tools:

• Social Network Analysis (UCINET) to model relocation diffusion links, centralities, and overall diffusion networks, enabling two-way transmission analysis and role reversals between source and target regions.
• GIS spatial analyses: Kernel Density Estimation to map accepted regions’ intensity over periods; Gravity Model Fij = K*(Ci*Cj)/d^b (K=1, b=1) to quantify spatial interaction strength and identify maximum gravitational lines, delineating core areas and interaction corridors; Gravity transform to track center-of-gravity movement (direction, distance, angle) over time; Standard Deviation Ellipse (SDE) to assess directional trends and dispersion. ArcGIS generated gravity, SDE, and related parameters. Outputs include period-wise centrality (Table 1 subset shown; full in S2), kernel density maps (Fig. 1), gravity interactions and maximum lines (Fig. 2; full in S3), acceptors’ native places (Fig. 3), gravity movement (Fig. 4; Table 2), SDE parameters (Table 3), and diffusion path diagrams (Fig. 5).

• Temporal phases: Yangmingism diffusion followed five stages—rise, peak, decline, revival, trough—matching general cultural diffusion cycles.
• Spatial structural evolution: Accepted regions transitioned through polycentric to localized ribbon–polycentric, then monocentric, polycentric, and finally fragmented distributions. Diffusion shifted from point–axis (along transport corridors) to core–periphery and back to point–axis as diffusion potential weakened.
• Core regions and distance decay: Diffusion displays distance decay, concentrated within Han cultural areas. Core areas are the Yangtze River Delta and the middle–lower Ganjiang basin (Ganzhou–Ji’an–Nanchang). Gravity analysis shows first- and second-level links and most third-level links cluster in these cores, forming a core–periphery spatial structure. Approximately 80% of acceptors’ native places lie south of the Yangtze, aligning with historical economic-cultural centers and academy density.
• Network centralities and accepted regions: 49 regions accepted Yangmingism, with varying in-/out-degrees in relocation diffusion. Examples: Yingtian (high in-degree), Shuntian (high acceptance and outward radiation), Guiyang and Shaoxing (strong out-degrees in certain periods), Ningguo and Weihui (high in-degree but weaker outward radiation), Ji’an and Hangzhou (balanced attract-radiate). Categories emerged where dissemination exceeded acceptance (e.g., Shaoxing, Guiyang, Nanchang, Ganzhou, Baoding), acceptance exceeded dissemination (e.g., Yingtian, Ningguo, Weihui), and balanced cases (e.g., Shuntian, Ji’an, Changzhou, Yangzhou, Hangzhou, Suzhou, Fuzhou).
• Diffusion centers by period: Rise—Guiyang, Ganzhou, Nanchang, Yingtian, Shaoxing; Peak—Shuntian, Yingtian, Ji’an, Shaoxing, Ningguo; Decline—Shaoxing (Jishan school), Changzhou as an accepted region (Donglin school focus on Zhuziology); Revival—Shaoxing (Huang Zongxi), Weihui (Sun Qifeng); Trough—no clear center, scattered low-intensity acceptance.
• Center-of-gravity movement and SDE (directionality, speed): From rise to peak, gravity moved ~180.06 km generally northeast; decline period moved further north (131.34 km; E–W 101.16 km, N–S 83.77 km; ~1.16 km/a). Revival shifted northwest (175.81 km; E–W −152.88 km, N–S 86.81 km; ~1.42 km/a). From revival to trough it shifted 283.93 km to the south bank of the Yangtze (E–W 114.25 km, N–S −259.93 km; ~1.07 km/a), with SDE flattening lowest (0.22) indicating dispersed acceptance. Overall diffusion speed cycled decreasing–increasing–decreasing, reflecting changing diffusion potential.
• Diffusion modes: Relocation diffusion dominates overall, with expansion diffusion secondary. At the peak, relocation diffusion strongly shaped spatial structure; about two-thirds of relocation diffusion involved national or regional political centers. Rise and revival had more balanced relocation and expansion; decline and trough periods were more expansion-driven due to reduced prestige and increased role of writings.
• Pathways and corridors: Principal channels included (1) Zhedong Canal–Qiantang–Fuchun–Lanjiang–Xinjiang–Poyang–Ganjiang connecting N Zhejiang and Jiangxi; (2) Beijing–Hangzhou Canal–Yangtze–Ganjiang linking the Yangtze River Delta and Jiangxi. Terrain and cultural resistance shaped paths: mountainous SE Zhejiang–Fujian impeded spread; strong Zhuziology in Fujian and North China resisted Yangmingism; distance attenuation limited spread into N Jiangsu and Shandong. Northern diffusion often centered on Shuntian, later radiating to Shandong, Henan, and along land routes toward Shaanxi; revival saw southward spread from Baoding to Weihui and gradual extension to Shanxi.
• Administrative hierarchy effects and reversals: During rise→peak, diffusion moved into higher administrative/cultural centers; during peak→decline, diffusion extended from higher to lower hierarchies. In relocation diffusion, roles of source and target regions can reverse due to stronger radiation of high-rank regions and cultural innovation in target regions facilitating backflow.

By operationalizing acceptance among Confucian scholars and integrating social network analysis with GIS, the study quantitatively reconstructs Yangmingism’s diffusion mechanisms across four centuries. The findings validate a five-phase diffusion trajectory and demonstrate how spatial structures evolve with changing diffusion potential. The prominence of relocation diffusion—especially via officials within the imperial bureaucracy—highlights institutional mobility as a key cultural vector. Distance decay, transport corridors (rivers, canals), and administrative hierarchies shaped the geography of spread, producing core–periphery dynamics centered in the Yangtze Delta and Ganjiang basin. The analysis also uncovers two-way transmission and role reversals between source and target regions, emphasizing interactive cultural exchange rather than one-way dissemination. These insights address the study’s aim to move beyond discursive and regional narratives, offering a spatially explicit, data-driven picture of religious-cultural diffusion within a single civilizational sphere. The results underscore how topography, communication infrastructure, prevailing intellectual traditions (e.g., Zhuziology), and institutional contexts modulate adoption patterns over time.

The study maps and quantifies the diffusion history of Yangmingism during the Ming–Qing eras, showing a five-stage temporal cycle and distinct spatial structural transitions from point–axis to core–periphery and back, with strong distance decay and core concentrations in the Yangtze River Delta and Ganjiang regions. Relocation diffusion predominated, mediated by scholarly and official mobility, with administrative hierarchies and cultural contexts guiding directions of spread and occasional reversals between source and target regions. Methodologically, combining social network centralities, gravity modeling, gravity transform, and SDE within GIS offers a robust framework for analyzing religious-cultural diffusion. Future research can expand beyond Confucian scholars to broader social groups, incorporate additional data sources, and refine models to better capture multi-scalar and multi-channel diffusion processes, including the roles of non-elite actors and textual dissemination.

The dataset focuses on Confucian scholar acceptors, underrepresenting broader societal adoption (peasants, workers, merchants). Source availability is uneven across regions and periods, leading to potential undercounting of acceptors and uncertainties for some accepted regions. The reliance on documented writings and biographical records may bias detection toward elite, literate actors and well-documented areas (e.g., cores). Diffusion types inferred from generational and textual links may miss informal or undocumented transmissions. The authors note plans to integrate new data sources and improve models to address these constraints.