Visualization analysis of academic software applied to traditional Chinese medicine research based on bibliometrics methods

Hongjin Wu , Shenguang Li , Weiwei Dai , Libo Wang , Jie Zhang , Chenglong Wang
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Abstract

Introduction

Academic research software played an increasingly critical role in traditional Chinese medicine (TCM). Studies have explored the usage and influence of software tools. However, few studies have quantified the impact of scientific software on TCM research using CiteSpace and VOSviewer.

Methods

Articles related to TCM research with software applications from 1991 to 2024 were searched from the core collection database of Web of Science (WOS) and CNKI database. EndNote software was used for initial data screening. The authors, countries, institutions, keyword co-occurrence, keywords burst were analyzed using CiteSpace and VOSviewer for constructing a knowledge map.

Results

A total of 35,981 articles related to relevant TCM research were obtained. The publications had shown an upward trend over the past decades. In 2022, the relevant publications reached an all-time high of 2734 (CNKI) and 1873 (WOS) articles. The top three journals with the most publications were “Medicine”, “Evidence-based complementary and alternative medicine”, “Frontiers in Pharmacology”. The top three scholars with the most articles were Liu Jianping, Lee Myeong Soo, and Liang Fangrong. China, United States, and England were major contributors to relevant TCM research. Beijing University of Chinese Medicine, China Academy Chinese Medical and Guangzhou University of Chinese Medicine were leading institutions in this field. Keywords analysis showed that hot spots and trends in relevant research mainly focusing on systematic review, alternative medicine, acupuncture, and TCM network pharmacology.

Discussion

This analysis identified the most influential authors, institutions, and countries in TCM research with software applications, and provided a reference for assessing their academic impact. The analysis of keywords and software applications was useful for analyzing research hotspots and their evolution, as well as for predicting future trends.

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