A Study on the Research Trend of Democratic Civic Education in Korea through Network Text Analysis

2020 ◽  
Vol 29 (3) ◽  
pp. 113-133
Author(s):  
Min-gyeom Kang
Keyword(s):  
Civic Education ◽  
Text Analysis ◽  
Research Trend ◽  
Network Text Analysis

scholarly journals Study on Business Ecosystem Research Trend Using Network Text Analysis

2021 ◽  
Vol 13 (19) ◽  
pp. 10727
Author(s):  
Matthew Minsuk Shin ◽  
Seunghye Jung ◽  
Jin Sung Rha
Keyword(s):  
Text Analysis ◽  
Betweenness Centrality ◽  
Research Trend ◽  
Degree Centrality ◽  
Ecosystem Research ◽  
Business Ecosystem ◽  
Network Text Analysis ◽  
Bibliographic Data ◽  
Centrality Analysis ◽  
New Phase

The management environment is moving into a new phase with the changing global circumstances. The business ecosystem as a management strategy has been studied for the last 30 years since the concept was introduced. The purpose of this study was to analyze the research trend in business ecosystem by using network next analysis and to understand the concept, being one that is still being actively studied. Network text analysis is a commonly used method to analyze research trends by forming networks based on bibliographic data of the articles, namely, keywords. For the analysis, we collected the data and keywords from 340 research papers published in global academic journals related to business ecosystem on the basis of the Scopus database. Through keywords extraction and cleansing, we found that the keywords of “innovation”, “sustainability”, and “platform” were mentioned most frequently, and the research topics were correlated to each other. Moreover, we conducted degree centrality and betweenness centrality analysis along with clustering analysis by transforming the two-mode network into a one-mode network. Degree centrality involves analyzing the degree to which one keyword links to other keywords, and betweenness centrality shows the mediating effects of a keyword to other keywords. In the centrality analysis results, “innovation”, “sustainability”, “platform”, and “business model” showed the highest degree centrality, and “sustainability”, “innovation”, “China”, and “platform” had the highest betweenness centrality. Then, we classified the clusters of subtopics into five groups. The current study examined accumulated research and suggested a comprehensive understanding of the research trend in business ecosystem by incorporating a method enabling research trend analysis to secure objectivity. This research is expected to help researchers to review the research trend in business ecosystem and identify expandable topics for further studies.

Text Analysis on the Research Trend of ‘Resilience’ in Korea : Focus on Climate Change and Urban Disaster

2019 ◽  
Vol 10 (4) ◽  
pp. 401-414 ◽  
Author(s):  
Gil Sang Lee ◽  
Dae Yong Jin ◽  
Seul Ki Song ◽  
Hee Sun Choi
Keyword(s):  
Climate Change ◽  
Text Analysis ◽  
Research Trend ◽  
Urban Disaster

scholarly journals Knowledge Graphs and Network Text Analysis

2003 ◽  
Vol 42 (1) ◽  
pp. 91-106 ◽  
Author(s):  
Roel Popping
Keyword(s):  
Present State ◽  
Text Analysis ◽  
Scientific Theory ◽  
Semantic Network ◽  
Labour Markets ◽  
Knowledge Graph ◽  
Causal Relations ◽  
Network Text Analysis ◽  
Knowledge Graphs

A knowledge graph is a kind of semantic network representing some scientific theory. The article describes the present state of this field and addresses a number of problems that have not yet been solved. These problems are implicit relations, strength of (causal) relations, and exclusiveness. Concepts might be too broad or complex to be used properly, so directions for solving these problems are explored. The solutions are applied to a knowledge graph in the field of labour markets.

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