Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

doi:10.1016/j.physa.2016.01.017

Cited by 181 publications

(79 citation statements)

References 41 publications

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“…Keywords co-occurrence can effectively reflect the research hotspots in the discipline fields, providing auxiliary support for scientific research [33]. In all the 988 MBD-related publications, we obtained 5591 keywords altogether.…”

Section: The Abstract Analysis Of Research Hotspots On Mbd Studymentioning

confidence: 99%

A Bibliometric Analysis and Visualization of Medical Big Data Research

et al. 2018

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With the rapid development of "Internet plus", medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as "all years". The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.

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Section: The Abstract Analysis Of Research Hotspots On Mbd Studymentioning

confidence: 99%

A Bibliometric Analysis and Visualization of Medical Big Data Research

et al. 2018

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“…Bibliometric analysis has been used for the detection of technological trends by means of keyword co-occurrence and network analysis [16], [23], [18]. Visualisation techniques have been applied effectively to explore themes, monitor trends and locate interrelated fields [25], [24].…”

Section: Methodology and Research Designmentioning

confidence: 99%

Identifying trends and flows in communication and information processing by means of keyword network analysis

Dotsika

Watkins²

2017

Proceedings of the 3rd International Conference on Communication and Information Processing

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“…Finally, Figure 4 illustrates the co-occurrence of keywords. For Li et al [67], co-occurrence addresses the hotspots for research in the discipline's fields, providing ancillary support for scientific research. In this analysis, the size of a node characterizes the number of articles published and a small distance between two journals reveals a higher frequency of citations [66].…”

Section: Network Analysismentioning

confidence: 99%

“…The distance between the nodes reflects the force of relationship between them. The thicker the line, the greater the co-occurrence [67,69] . It can be seen in the above figure, therefore, that the words with greater frequency and total strength of the link of the nodes were "machine learning," "smart city," "model," "data mining," "consumption," "prediction," "China", and "energy efficiency".…”

Section: Network Analysismentioning

confidence: 99%

Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018

et al. 2019

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Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.

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Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

Cited by 181 publications

References 41 publications

A Bibliometric Analysis and Visualization of Medical Big Data Research

A Bibliometric Analysis and Visualization of Medical Big Data Research

Identifying trends and flows in communication and information processing by means of keyword network analysis

Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018

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