• Korean Journal of Occupational Health Nursing
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• v.24 no.2
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• pp.76-85
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• 2015

Purpose: The purpose of this study was to identify knowledge structure of the Korean Journal of Occupational Health Nursing from 1991 to 2014. Methods: 400 articles between 1991 and 2014 were collected. 1,369 keywords as noun phrases were extracted from articles and standardized for analysis. Co-occurrence matrix was generated via a cosine similarity measure, then the network was analyzed and visualized using PFNet. Also NodeXL was applied to visualize intellectual interchanges among keywords. Results: According to the results of the content analysis and the cluster analysis of author keywords from the Korean Journal of Occupational Health Nursing articles, 7 most important research topics of the journal were 'Workers & Work-related Health Problem', 'Recognition & Preventive Health Behaviors', 'Health Promotion & Quality of Life', 'Occupational Health Nursing & Management', 'Clinical Nursing Environment', 'Caregivers and Social Support', and 'Job Satisfaction, Stress & Performance'. Newly emerging topics for 4-year period units were observed as research trends. Conclusion: Through this study, the knowledge structure of the Korean Journal of Occupational Health Nursing was identified. The network analysis of this study will be useful for identifying the knowledge structure as well as finding general view and current research trends. Furthermore, The results of this study could be utilized to seek the research direction in the Korean Journal of Occupational Health Nursing.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.274-284
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• 2019

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.53-59
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• 2022

The purpose of this study is to examine the factors related to learning through analysis of domestic research trends in literacy and to present the direction of literacy education. Research papers from 1993 to February 2022 were collected using RISS. 'Literacy' and 'Education' were used as search keywords, and 200 papers were selected for analysis. As a result of analysis using keyword network analysis, 118 keywords appeared at least three times out of a total of 810 keywords. The order of the keywords with the highest frequency is 'digital literacy', 'media literacy', and 'elementary school'. The following direction was suggested through the analysis results. First, it is required to establish an online teaching and learning resource platform and link it with education policy. Second, it is necessary to set literacy competencies and seek ways to improve competencies. Third, a digital-based convergence education model should be developed. This study is meaningful in that it analyzed the most recent literacy studies and suggested the direction of literacy education.

• 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.

• Knowledge Management Research
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• v.17 no.1
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• pp.1-16
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• 2016

The purpose of this study is to analyze 352 scholarly journals and 1496 keywords in Knowledge Management Research from 2000 to 2015 and provide systematical view point of research trend in the area of knowledge management using graph theory and network model. The relational patterns among keywords as well as keywords which recently received noticeable attention and keywords which receded from the spotlight in recent years in the knowledge management literature were identified. The result of this study can be used as a foundation of future research ideas in knowledge management.

• Journal of IKEEE
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• v.14 no.4
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• pp.305-311
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• 2010

Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.577-584
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• 2020

Construction automation and robotics have been widely adopted in the construction industry as a promising solution to such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. The analysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledge elements and possible future research directions. This study attempts to (1) construct keyword networks from the papers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigate how keywords and keyword communities are associated with each other, and (3) examine the changes in the crucial keywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Building construction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends show that research themes related to Infrastructure, Construction equipment, and 3D have consistently received a large amount of attention, regardless of geographical region. Research on as-built status model utilization through BIM and Laser scanning and improving Energy performance is taking place more frequently. In contrast, research studies related to problem-solving based on Neural networks are not as common as previously. This study provides useful insights into the construction automation field, at both the macro and micro levels.

• The Journal of Industrial Distribution & Business
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• v.10 no.8
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• pp.17-24
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• 2019

Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

• Women's Health Nursing
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• v.29 no.2
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• pp.128-136
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• 2023

Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women's health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling. Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling. Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: "gynecologic neoplasms," "menopausal health," "health behavior," "infertility," "women's health in transition," and "nursing education for women." Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women's health is evolving with changing times and warrants further progress in the future. Future research on women's health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

• Journal of Elementary Mathematics Education in Korea
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• v.23 no.4
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• pp.459-479
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• 2019

The purpose of this study is to explore the research trends and knowledge structures of 『Journal of Elementary Mathematics Education in Korea』 by applying the keyword network analysis. To do this, we analyzed the frequency of the occurrence of keywords in the journal and conducted keyword network analysis using the Krkwic program and NodeXL program. The results of the analysis are as follows. Firstly, 749 keywords were extracted from keyword cleansing process and 48 keywords, including mathematics curriculum, mathematics textbooks, school mathematics, mathematical problem solving, mathematically gifted student, etc. appeared more than five times. Secondly, the keyword network analysis showed that the keywords-mathematics textbooks, school mathematics, mathematical problem solving, mathematical communications-have high connection centrality. Finally, we provided the limitations of this study and suggested future research.