Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after “the Thanks to You Challenge” during the COVID-19 Pandemic

2021 ◽  
Vol 51 (4) ◽  
pp. 442
Author(s):  
Eun Kyoung Yun ◽  
Jung Ok Kim ◽  
Hye Min Byun ◽  
Guk Geun Lee
2021 ◽  
Vol 104 (4) ◽  
pp. 003685042110619
Author(s):  
Ji-Su Kim ◽  
Hyejin Kim ◽  
Eunkyung Lee ◽  
Yeji Seo

This study aimed to identify the relationships between the keywords of research on metabolic syndrome in cancer survivors and the entire knowledge research structure, through topic extraction from a macro perspective. From six electronic databases, 918 studies published between 1996 and 2019 were identified and reviewed, and 365 were included. Keyword network analysis and topic modeling were applied to examine the studies. In keyword network analysis, “obesity,” “treatment,” “breast cancer,” “body mass index,” and “prostate cancer” were the major keywords, whereas “obesity” and “breast” were the dominant keywords and ranked high in frequency, degree centrality, and betweenness centrality. In topic modeling, five clustered topics emerged, namely metabolic syndrome component, post CTX(chemotherapy) sequence, prostate-specific antigen-sensitive plot, lifestyle formation, and insulin fluctuation. Topic 2, post CTX sequence, showed the highest salience in earlier studies, but this has decreased over time, and the themes of the studies have also broadened. This study may provide critical basic data for determining the changing trends of research on metabolic syndrome in cancer survivors and for predicting the direction of future research through the visualization of the effects and interactions between the major keywords in research on metabolic syndrome in cancer survivors.


2021 ◽  
pp. 1-7

Background and purpose: Information on topics and knowledge structures is an important indicator of trends, prospects and sustainability in research fields. Although many studies on physical activity (PA) have been published in Korea, no studies have been reported to explain knowledge structure (KS) and keyword topics. Therefore, this study intends to analyze and explain PA-related studies. Research method: In this study, topic modeling and keyword network analysis were applied to explore the KS of domestic PA-related studies published in domestic journals. 83 journals and 782 studies published from 1996 to June 2019 were collected, and 5441 key research keywords were used as data. Results and Conclusions: Analyzing the study of physical activity in Korea, first, it is a study that reports the PA level of students from an educational point of view. Second, it is a study that verified the validity and reliability of the measurement tool. Third, a study reporting the psychological and behavioral characteristics of PA participants. Fourth, studies promoting PA participation in subjects with disabilities. Fifth, research on key topics of health and obesity is ongoing. This study can be used as basic data to explore the current status of global PA research by providing information on major themes, keywords, and trends of domestic PA research.


2019 ◽  
Vol 11 (11) ◽  
pp. 3155 ◽  
Author(s):  
Kyunghun Min ◽  
Moonyoung Yoon ◽  
Katsunori Furuya

The aim of this study was to explore the keywords related to smart city concepts, and to understand their flow. This research used a keyword network analysis by collecting keywords from papers published on the web from Scopus, which is an international scholarly papers engine. The data were collected from before and after 2016, and since the amount of data has been growing rapidly after global agreements such as the United Nations’ Sustainable Development Goals (SDGs) in 2015, we attempted to focus on adjacent years of publication. In order to understand the flow of research, we conducted a central analysis, which is widely used in quantitative research relating to social network analysis, and performed cluster analysis to identify relationships with related research. The results of the analysis are represented in the form of network maps, and the role of each keyword was clarified based on these network maps. In addition, the overall flow explained the change of flow through discarded and emerging keywords, and the relationships with related fields were explained through cluster analysis. The findings could serve as a basis for policymakers, urban managers, and researchers seeking a comprehensive understanding of the smart city concept in urban planning areas.


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