Domestic Research Trends in Digital Writing Using Text Network Analysis

2021 ◽  
Vol 43 (1) ◽  
pp. 603-624
Author(s):  
Jiyoung Lee
Keyword(s):  
Network Analysis ◽  
Research Trends ◽  
Digital Writing ◽  
Text Network Analysis

Bibliometric Analysis on the Research Trends in the Journal of Korean Society of Beauty and Arts using Text Network Analysis

2020 ◽  
Vol 21 (3) ◽  
pp. 127-141
Author(s):  
Shin-Hee Kim
Keyword(s):  
Network Analysis ◽  
Bibliometric Analysis ◽  
Growth Period ◽  
Research Trends ◽  
Actual State ◽  
Expression Recognition ◽  
Korean Society ◽  
Research Stream ◽  
New Research ◽  
Text Network Analysis

The purpose of this study is to identify the research stream and trend in the field of beauty by using bibliometric analysis based on text network analysis. 792 research papers that had been published in The Korean Society of Beauty and Arts from 2008 to 2019 were collected and network analysis was conducted through text mining, pre-processing, purifying of data. key findings are as follows. First, the quantitative and qualitative aspects of the research have improved since 2016, and methodology focused on the words such as influence, use, effect expression, recognition, change, comparison, performance, and actual state. Second, during the introduction period, researches focused on identifying the effects of certain issues related to beauty for women. Third, research methodologies were diversified during the growth period, and business studies related to the satisfaction of beauty services were increased. Fourth, it was expanded to the researches on service satisfaction and follow-up behavior and researches on psychological aspects in the period of maturity. This study is valuable in that it provides useful information that is required for the new research in the beauty field, along with identifying existing research trends.

scholarly journals A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling

2021 ◽  
Vol 27 (2) ◽  
pp. 175-185
Author(s):  
Junglim Lee ◽  
Youngji Kim ◽  
Eunju Kwak ◽  
Seungmi Park
Keyword(s):  
Diabetes Mellitus ◽  
Cardiovascular Disease ◽  
Network Analysis ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Topic Modeling ◽  
Diabetes Management ◽  
Research Trends ◽  
The Past ◽  
Text Network Analysis

Purpose: The aim of this study was to identify core keywords and topic groups in the ‘Gestational diabetes mellitus (GDM) and Breastfeeding’ field of research for better understanding research trends in the past 20 years.Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups.Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', ‘fetus’, ‘hypoglycemia’, 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were ‘cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: ‘cardiovascular disease’, ‘obesity’, ‘complication prevention strategy’, ‘support of breastfeeding’, ‘educational program’ and ‘management of GDM’.Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.

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