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. 2025 Jul 10:19:1636904.
doi: 10.3389/fnins.2025.1636904. eCollection 2025.

Bibliometric and visualization analysis of hydrogel research in spinal cord injury: comparative study of Chinese and English literature

Wenju Bai  1 , Xiaoyuan Huang  2 , Jian Liu  3 , Kamiran Halike  2 , Jinyong Li  4 , Xv Zhang  4 , Tengwu Chang  2 , Jichao Wang  1
Affiliations

Bibliometric and visualization analysis of hydrogel research in spinal cord injury: comparative study of Chinese and English literature

Wenju Bai et al. Front Neurosci. .

Abstract

Background: Over the past decade, the fields of hydrogel and spinal cord injury (SCI) research have witnessed rapid development. To explore disparities between China and global trends in hydrogel research, this study systematically conducted qualitative and quantitative analyses of related publications, summarizing current research foci and future directions. This provides critical guidance for researchers to delve deeper into hydrogel applications.

Methods: A total of 866 records in the hydrogel and SCI domains were collected from the Web of Science Core Collection (WoSCC) and China National Knowledge Infrastructure (CNKI) between 2014 and 2024. CiteSpace, VOSviewer, SCImago, and the R package "bibliometrix" were utilized to analyze regional distributions, institutional collaborations, journal impacts, author productivity, and keyword trends.

Results: Annual publications in hydrogel and SCI research exhibited consistent growth. China (n = 382) and the United States (n = 158) collectively contributed 76.2% of global academic output, reflecting disproportionate productivity. Zhejiang University and Jinan University demonstrated significant contributions across international and Chinese academic platforms. XIAO Jian distinguished himself through exceptional metrics (h-index, total citations), establishing his prominence as a high-impact scholar. BIOMATERIALS emerged as the most prolific and influential journal based on total link strength. Keyword and co-citation analyses revealed heightened emphasis on 3D bioprinting and electroactive bio-scaffolds in both WoSCC and CNKI databases. Systemic research disparities reveals that CNKI prioritize hydrogel technologies with a distinctive focus on indigenous specializations (e.g., Chuanxiongzine and stem cell transplantation), while WoSCC demonstrates notable advantages in establishing therapeutic loops encompassing drug delivery systems, functional recovery evaluation, and neuroimmune modulation strategies.

Conclusion: By integrating WoSCC and CNKI data, this study comprehensively elucidates geographical disparities in research priorities between China and the global scientific community regarding hydrogel-mediated SCI repair, thereby proposing an evidence-based framework for international collaborative innovation. These insights offer valuable references to guide future hydrogel research.

Keywords: CiteSpace; bibliometric; comparative study; cord injury; hydrogel; visual analysis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Flowchart depicting a literature review process from CNKI and WoS Core Collection. Initial literature numbers were 214 and 736, respectively. After exclusions, numbers narrowed to 158 and 708. Exclusions included meeting abstracts, corrections, etc. Subsequent analysis involves bibliometrics, visualization, and analyses of country/region, affiliated institution, author, journal, keyword, and references.
FIGURE 1
Flowchart of the article search.
Chart A displays annual publications from 2014 to 2024, with the CNKI (green) showing a steeper increase than WoS (blue). Trendlines indicate the CNKI growth equation is \(y = 10.282x + 1.7636\), \(R^2 = 0.9265\), and for WoS, \(y = 2.7182x - 2.1273\), \(R^2 = 0.7311\). Chart B shows annual citations for WoS, starting at 14 in 2014 and rising to 5710 in 2024, following a polynomial trend \(y = 60.214x^2 - 158.96x + 170.41\), \(R^2 = 0.9989\).
FIGURE 2
(A) Annual scientific publications and linear trends of CNKI and WoS (2014–2024). (B) Annual citation trends of WoS-indexed publications (2014–2024) with quadratic regression.
Map and network visualizations depict international document collaboration. The map shows document distribution, with larger circles representing more documents in the U.S., China, and other countries. The network diagram illustrates connections between countries, highlighting strong links between the U.S. and China, using colored lines to indicate link strength. Labels identify each country.
FIGURE 3
(A) Geographic network map of hydrogel and spinal cord injury research. (B) International research collaboration network. Node size proportional to the number of joint publications and edge thickness reflecting total link strength.
Three network visualizations depict academic collaborations. A: A colorful network map with nodes labeled by university names, showing dense connections. B: A similar map with names of research field authors, also color-coded and interconnected. C: A faded network displaying names in Chinese, organized spatially, and less dense than the others.
FIGURE 4
(A) Visualization analysis of institutional collaboration in VOSviewer. (B) Author collaboration analysis of the WoSCC database. (C) Author collaboration analysis in the CNKI database.
Diagram with three sections: A) A colorful circular chart displaying percentages and labels of various journals, with a legend on the right for color identification. B) A network map showing interconnected journal names in red, green, and blue clusters, highlighting “biomaterials” centrally. C) Two opposing clusters labeled “Citing Journals” and “Cited Journals,” connected by colored lines indicating citation relationships.
FIGURE 5
(A) Proportional distribution of journals donut chart. (B) Journal collaboration analysis of the WoSCC database. (C) The dual-map overlay of journals related to hydrogel and spinal cord injury research.
CiteSpace visualizations display two graphs. The top graph (A) shows a network map with clusters labeled by topics such as “motor neuron recovery” and “biomaterial scaffold,” each in different colors. The bottom graph (B) features a timeline view with colored nodes representing these topics over the years 2009 to 2024. Both graphs include a color-coded legend and timeline bar indicating publication years.
FIGURE 6
(A) Clustering analysis of keyword co-occurrence networks in WoSCC. (B) Top 17 keywords with the strongest citation bursts based on WoSCC. (C) Clustering analysis of keyword co-occurrence networks in CNKI. (D) Top 11 keywords with the strongest citation bursts based on CNKI.
“Graphic displaying two visualizations labeled A and B. A shows interconnected clusters highlighting topics like” “electroactive bioscaffold,” “spinal cord,” and “motor neuron recovery,” each with distinct colors. B features a timeline from 2009 to 2024 with bubble diagrams representing research areas over time, using a color gradient to indicate different years. Both visuals include a legend linking colors to specific research topics and are produced using CiteSpace software.”
FIGURE 7
(A) CiteSpace visualization of co-cited literature clustering (B) Timeline view of these co-cited reference clusters.
Two treemaps compare research topics by prevalence. Panel A shows English terms: “spinal cord injury” dominates at 29%, followed by “hydrogel” at 11%. Panel B shows Chinese terms: similarly, “spinal cord injury” leads at 30%, with “水凝胶” (hydrogel) at 10%. Each topic includes a percentage and count, indicating its representation in the dataset.
FIGURE 8
(A) Top 50 keywords in the field of hydrogels and spinal cord injury based on WoSCC (B) Top 50 keywords in the field of hydrogels and spinal cord injury based on CNKI.
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