• Korea Real Estate Review
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• v.27 no.3
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• pp.51-70
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• 2017

This study aimed to measure street centralities with the street width, and to analyze their effects on the residential and non-residential land prices in Seoul, South Korea. Most of the studies on urban economics and policy focusing on the urban spatial structure have evolved in terms of their perspective from monocentric to polycentric models. Recently, their themes shifted to measuring street centralities and capturing their effects on urban phenomena. To expand the existing studies and discussion, this study analyzed the street centralities with the street width, and how they changed the land prices. Multilevel regression models generated a few key findings relevant to the relationship between street centralities and land prices. While a higher detour volume and closeness to wider streets commanded premium residential land prices, higher visibility and detour volume to wider streets were associated with higher non-residential land prices. These findings suggest a robust connection between street configuration and near-land prices. Thus, the results of this study suggest a few insightful policy implications for urban planners, urban designers, real estate developers, and appraisers.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.68-74
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• 2019

The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.91-98
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• 2019

The present study was performed to investigate the general research trends of dyslexia and learning disability to explore the centrality of related variables though analysis of keyword networks. Data were collected from ten years articles research information sharing service(RISS) which is provided by korea education and research information service(KERIS). The research subjects selected for the analysis were keyword cleansing work, extraction major keyword using KrKwic program and using NodeXL program to Visualize the center of connection between keyword. The results of this were as follows. First, totally 72 of keyword were extracted from keyword cleansing process and among those keyword. major keywords included learning disability, dyslexia, RTI. Second, analysis of the betweenness centrality of dyslexia and learing disabilities shows that learning disabilities are a key word that has been addressed in the study of dyslexia and learning disabilities in korea. The results of these studies suggest a method of analyzing trends in qualitative and qualitative analysis in relation to dyslexia and learning disorder.

• Smart Media Journal
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• v.11 no.8
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• pp.73-83
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• 2022

In order to support new construction engineering companies with weak information power to successfully advance into the overseas construction market, this study tried to analyze what are the keywords of interest in the overseas construction market and how they differ from Korea. For this purpose, we recently collected 2,473 news article titles and major articles targeting smart cities that are of high interest in Korea and Vietnam. Through network configuration and topic modeling, we examined the connection relationship between the word of interest and the word of interest. In addition, the influence of the word of interest in the network was measured using PageRank centrality. Through this analysis, it was found that there is a high interest in smart city-related construction, cities, and digital in both countries, and the difference in terms of interest between Korea and Vietnam was inferred. Finally, the limitations of this study and additional research directions to complement them are presented.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.111-119
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• 2022

The purpose of this paper is to examine the change in perception of 3D virtual fashion before and after COVID-19 using big data analysis. The data collection period is from January 1, 2017, before the outbreak of COVID-19, to October 30, 2022, after the outbreak. Big data was collected for key words related to 3D virtual fashion extracted from social media such as Naver, Daum, Google, and YouTube using Textom. After the collected words were refined, word cloud, word frequency, connection centrality, network visualization, and CONCOR analysis were performed. As a result of extracting and analyzing 32,461 words with 3D virtual fashion as a keyword, the frequency and centrality of fashion, virtual, and technology appeared the highest, and the frequency of appearance of digital, design, clothing, utilization, and manufacturing was also high. Through this, it was found that 3D virtual fashion is being used throughout the industry along with the development of technology. In particular, the key words that stand out the most after COVID-19 are metaverse and 3D education, which are in high demand in the fashion industry.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.285-302
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• 2023

Based on this study, the research trends were identified for the field of public libraries in Korea by utilizing the keyword network analysis. For 20 years from 2003 to 2022, a total of 752 papers related to the public libraries published in the four largest academic journals in the field of library and information science in Korea were analyzed. The research results are as follows. First, from 2003 to 2022, an annual average of 37.6 papers were published, demonstrating a pattern of repeated rise and fall. Second, the keywords of 'service' and 'culture' were identified as the most discussed keywords as they were found to be among the top five in terms of the frequency of occurrence, connection centrality, and the mediation centrality analysis results. Third, in terms of the results of analyzing the co-occurrence frequency of keyword pairs, attention was paid to the keyword pairs of education-program, service-user, service-children, and service-disability.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.162-171
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• 2020

The purpose of this study is to examine the social perception of disaster safety education for young children based on Textom big data and to explore the direction of young children's disaster safety education. Researchers collected and analyzed online text data using the keywords 'young children+disaster+safety education' from portal websites from 2014 to 2017. The raw data were then subjected to first and second data refinement process. Based on the frequency analysis results, 50 keywords were selected, and the selected keywords were converted into matrix data for network analysis. The results of the study are: first, the most frequently appeared keyword together with young children's disaster safety education was 'education', followed by 'experience', 'kindergarten', 'prevention', and 'school.' Second, keywords with high centrality in the analysis of centrality also were 'education', 'experience', and 'prevention'. In addition, keywords like 'prevention', 'life', and 'evacuation' appear higher in connection-centricity than frequency ranking, which means that the degree of connection between the words is high. These results suggest that young children need education in during early childhood in order to improve their disaster safety skills, and disaster safety education should be accomplished through 'prevention' and 'experience' in early childhood education institutions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.601-609
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• 2018

The Smart City Plan specifies that it should reflect the content of the Smart City Comprehensive Plan, which is the upper plan while presenting the basic direction, promotion strategy, service establishment and operation plans of a smart city construction project. However, there are not enough empirical studies on whether plan contents are systematically established according to smart city planning hierarchy. In this study, we are to use the social network analysis to find out the local government's smart city plan is actually highly connected to the Smart City Comprehensive Plan, a master plan at national level. To this end, we conducted a social network analysis on Gwangmyeong and Chuncheon, which were recently approved for smart city planning. First, 108 keywords were derived from the 2nd Smart City Comprehensive Plan, and the connectivity between these keywords and Smart City Planning was analyzed. The results of the social network analysis showed that the total connections of Smart City Planning in Gwangmyeong was 371, which was higher than 307 in Chuncheon, and the average degree of connection per keyword and network density were also higher in the Gwangmyeong Smart City Planning than the Chuncheon Smart City Planning. The results of the study showed that the Smart City Planning actually had a high connectivity with the Smart City Comprehensive Plan, and the keywords with high connection centrality were different for each local government. The result of this study can be used as a basis for judging whether there is a high correlation between plans.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.105-124
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• 2023

The purpose of this study was to identify the characteristics of the contents included in the curriculum and 382 syllabi of the department of home economics education of College of Education in Korea and analyze the correlation by detailed area through the keyword network method. In order to analyze the home economics education curriculum and 382 syllabuses of a total of 11 universities, the frequency of keyword occurrence was analyzed using the KrKwic program, also the degree of connection between keywords and various centrality scales were calculated and visualized. The results of this study were as follows. First, as a result of analyzing the entire syllabi, keywords representing various fields such as family, secondary school, clothing, food, consumer, and design appeared evenly, and keywords related to teaching methods such as 'method', 'practice', 'change', and 'principle' were appeared. Those keywords showed high degree of connection and centrality. Second, in the detailed sectoral analysis, core keywords for each area appeared, and each subject were found to reflect the core keywords of the academic base. This study contributes to the conversion of curriculum of the department of home economics education to future-oriented and convergent curriculum.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.