Mapping disciplinary differences of knowledge production and collaboration networks in China

Wei, Chen; Wang, Nyuying; Liu, Zhigao

doi:10.1080/21681376.2020.1771201

Cited by 12 publications

(13 citation statements)

References 7 publications

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“…7, and if it is above 0. 5, the clustering is generally considered reasonable [4] . In this study, all CiteSpace analysis results were signi cant and reasonable.…”

Section: Discussionmentioning

confidence: 98%

“…In this paper, we analyze the data with the help of CiteSpace developed by Dr. Chaomei Chen, and Excel software analysis. Citespace is an information visualization software mainly used for measuring and analyzing scienti c literature data, mainly based on co-citation analysis theory and path nding network algorithm and more [4] , to perform visual analysis of co-occurrence networks as well as clustering, journal bipartite graph overlay and literature and keyword burst intensity analysis, and to mine the key paths of subject area evolution and its important nodes through its results. We analyze the progress and trends of research in this eld during the last two decades by measuring the research literature related to the application of ML in the eld of TCM.…”

Section: Introductionmentioning

confidence: 99%

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A Bibliometric Analysis of CiteSpace-Based Machine Learning Research in Chinese Medicine

An,

Qi,

Lin

et al. 2023

Preprint

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Artificial intelligence (AI) is widely used in various fields, among which machine learning (ML) is the core of AI that can be rapidly updated and developed. ML has been continuously applied to the field of traditional Chinese medicine (TCM) in the past decades, and it has also attracted more and more attention. This study uses CiteSpace and Excel software to explore the development trends and research hotspots of TCM combined with ML. The Web of Science core database was searched using ML algorithms and TCM. The annual publication volume, country (region), institution, author, journal, cited literature, and keywords were analyzed. The results of the study showed that China contributed the most publications, with 95% of the literature originating from China, followed by the United States. The most prolific institution and authors belonged to the Shanghai University of Traditional Chinese Medicine. Evidence Based Complementary and Alternative Medicine was the most focused publication in this research area. The burst detection by cited literature and keywords shows that convolutional neural networks and tongue images as diagnostic methods are the current research hotspots in this field.

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“…7, and if it is above 0. 5, the clustering is generally considered reasonable [4] . In this study, all CiteSpace analysis results were signi cant and reasonable.…”

Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

A Bibliometric Analysis of CiteSpace-Based Machine Learning Research in Chinese Medicine

An,

Qi,

Lin

et al. 2023

Preprint

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“…Although we use highway traffic flows to delineate the spatial boundaries of megaregional regions in China at the scale of the prefecture level and above the city, the intercity traffic flow used in this study just represents one type of intercity flows and the results are still preliminary. In the future, we still need to combine multiple-source data of networks and flows for complement and cross-checking [43,44] and then comprehensively evaluate the spatial boundaries of megaregions based on the knowledge of the regional background.…”

Section: Discussionmentioning

confidence: 99%

Delineating the Spatial Boundaries of Megaregions in China: A City Network Perspective

Chen

2021

Complexity

Self Cite

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Globalization and informatization have significantly reshaped the map of the global economy. Mega cities and regions have become the battlegrounds in the interplay between globalization and localization, with megaregions becoming the most globally significant spatial configurations in this regard. However, academics and government departments disagree on how to define the spatial boundaries of megaregions. In this study, on the basis of highway traffic flow data between cities, we integrate the community detection and core-periphery profile algorithms to characterize the city networks in China and identify the city groups and delineate the core structures of city groups, which are the underlying megaregional structures in China. Based on this, we identify 21 megaregions among city groups in China, including the Yangtze River Delta, Pearl River Delta, Beijing-Tianjin-Hebei, and Chengdu-Chongqing megaregions, and preliminarily delineate their spatial boundaries. On the whole, there are spatial differences among China’s megaregions to a certain extent. Central and eastern China have numerous, large, and a high density of megaregions, while the western region has relatively few megaregions. The latter also differs notably from mature megaregions in terms of rank sizes, urban systems, and functional divisions of labor. Generally, this study develops a novel analytical framework for identifying the functional regions of megaregional space in China from a perspective of relational geography, with methodological implications for other fields of inquiry.

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“…The organization and distribution of significant literature are sorted out using bibliometrics and knowledge mapping, which also highlight the field's development and frontiers (Chen et al, 2015). CiteSpace 6.1.R2, a visual bibliometric software developed by Professor Chaomei Chen of Drexel University in the United States, is used to conduct this study.…”

Section: Data Source and Methodsmentioning

confidence: 99%

The Academic Landscape and Development of City Brand Image Research in China: Visualization based on the CiteSpace Scientific Knowledge Map

Ren,

Mustafa

2023

IJARBSS

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Since the 1990s, the accelerated urbanization process in China has prompted the theoretical research on Chinese city brand image. While numerous articles on city brand image research have been published in China, most of them are in Chinese and have limited global impact. This study utilizes the bibliometric software CiteSpace to conduct systematic visualization analysis and data interpretation of core journal papers in the field of urban image in the China National Knowledge Infrastructure (CNKI) database. It aims to present the fundamental characteristics, research topics, and development trajectory of Chinese scholars in this field, as well as identify future directions.The research reveals that China's city image theory research originated in the late 19th century, with increasing research interest observed since 2009. Both authors and institutions have yet to form a closely-knit collaborative network, with the majority of research conducted independently. The research topics primarily focus on the impact of major events on city image, the construction of city image media, city image design, and city culture. In terms of research trends, city image communication is identified as the main area of future city brand image research.The value of this study lies in enhancing the understanding of Chinese city brand image research among English-speaking scholars, students, and professionals, providing inspiration and guidance for their future research endeavors.

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Mapping disciplinary differences of knowledge production and collaboration networks in China

Cited by 12 publications

References 7 publications

A Bibliometric Analysis of CiteSpace-Based Machine Learning Research in Chinese Medicine

A Bibliometric Analysis of CiteSpace-Based Machine Learning Research in Chinese Medicine

Delineating the Spatial Boundaries of Megaregions in China: A City Network Perspective

The Academic Landscape and Development of City Brand Image Research in China: Visualization based on the CiteSpace Scientific Knowledge Map

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