• Journal of Science Education
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• v.40 no.3
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• pp.267-286
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• 2016

The study aimed to investigate a research trend in science gifted education of six years from 2010 to 2015 by utilizing literature analysis and Social Network Analysis (SNA) methods. In this study, 275 papers published in eight major academic journals of science education and gifted education were selected as research subjects. First, through the literature analysis, it was found that the most frequent research topics were cognitive characteristics (25.8%), curriculum/programs (22.6%), and social and emotional characteristics (20.2%). For the research method employed in research papers, the survey research (46.5%) was appeared as the most frequently employed method, and followed by experimental (18.8%), program development (10.6%), correlation (10.3%), and qualitative (6.4%) research methods. The most frequent research subject was appeared as middle school students (33.7%) and followed by elementary school (30.6%), and high school (12.7%) students. Second, the SNA method was utilized for producing keyword frequency, degree centrality and network analyses. It was appeared that the most common keywords over six years included 'science gifted', 'gifted education', and 'creativity' and frequent keywords were science gifted, gifted education, gifted, creativity, science inquiry, perception, (creative) problem solving, science high school, scientific attitude, and STEAM. Third, through 2-mode network analysis, it was found that the research papers about cognitive characteristics were mainly related to perceptions, thinking ability, scientific argumentation, science inquiry and so on. It was also found that the research papers about social and emotional characteristics were related to correlation, motivation, creativity-character, self-efficiency and so on. It was concluded that the SNA method can be performed with literature analysis together for better understandings and interpretations of the research trend of science gifted education in-depth.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.135-161
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• 2023

This study analyzed the research trends of COVID-19 research papers published in medical journals of Korea. Data were collected from 25 MEDLINE journals in 'Medicine and Pharmacy' studies and a total of 800 were selected. As a result of the study, authors from domestic affiliations made up 76.96% of the total, and the proportion of authors from foreign institutions decreased without significant change. The authors' majors were 'Internal Medicine' (32.85%), 'Preventive Medicine/Occupational and Environmental Medicine' (16.23%), 'Radiology' (5.74%), and 'Pediatrics' (5.50%), and 435 (54.38%) papers were collaborative research. As for author keywords, 'COVID19' (674), 'SARSCoV2' (245), 'Coronavirus' (81), and 'Vaccine' (80) were derived as top keywords. There were six words that appeared throughout the entire period: 'COVID19,' 'SARSCoV2,' 'Coronavirus,' 'Korea,' 'Pandemic,' and 'Mortality.' Co-occurrence network analysis was conducted on MeSH terms and author keywords, and common keywords such as 'covid-19,' 'sars-cov-2,' and 'public health' were derived. In topic modeling, five topics were identified, including 'Vaccination,' 'COVID-19 outbreak status,' 'Omicron variant,' 'Mental health, control measures,' and 'Transmission and control in Korea.' Through this study, it was possible to identify the research areas and major keywords by year of COVID-19 research papers published during the 'Public Health Emergency of International Concern (PHEIC).'

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.313-334
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• 2021

This study aimed to analyze AI research trends related to elementary, middle, and high school education. To this end, the related literature was collected from the SCOPUS database and the publication period of the collected literature was from 1974 to March 2021, with 154 journal papers and 571 conference papers. Research trends were analyzed based on the co-occurrences analysis technique of 4,521 words of author keyword and index keyword included in these papers. As a result of the analysis, big data, data mining, data science and deep learning were found as the latest research trends with machine learning and there was a difference between elementary, middle and high school education. It can be seen that elementary school had a lot of robot-related research, middle school had a lot of game and data-related research, and high school had various and in-depth research. In discussion, we mapped the top 50 words common to elementary, middle, and high schools with the 'Artificial Intelligence Basics' curriculum of Korean Government and '5 Big Ideas' of the United States Government so that AI research can be viewed at a glance.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• Korea Trade Review
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• v.44 no.5
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• pp.1-16
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• 2019

As the activities of global enterprises have become more globalized and the labor movement among nations has increased, many studies have been carried out on the effective adjustment of expatriate managers. By examining the literature over the past 30 years on the adjustment of expatriate managers, this study identified major research trends and presented future research directions. While prior studies have often been cumbersome, time-consuming, and dependent on the researchers' subjective judgments, this study performs a bibliometric analysis using quantitative and visualized reference materials to provide a map showing the evolution process of existing research on the adjustment of expatriates. Using the CiteSpace program, this study conducted a bibliometric analysis of 517 papers focusing on major research trends, research countries, research institutions, authors, and journals. Study results found that the study of international adjustment was mainly focused on self-directed senders, attribution adaptations, and personal characteristics. The United States, Britain, and Australia were the most represented countries, while the most influential institutions included Aarhus University, the University of Wisconsin, and Hong Kong Baptist University. As one of the leading researchers, Selmer of Orhuss University published 19 papers, followed by Luring of Orhuss University. The Journal of International Business Studies (JIBs) most frequently featured studies of overseas expatriate adjustment.

• Korean small business review
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• v.43 no.1
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• pp.131-145
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• 2021

This study aims to diagnose research trends and to deduct implications from meta analysis of entrepreneurship studies in the Asia Pacific Journal of Small Business (APJSB), one of the most well-known academic journals in management and entrepreneurship field in Korea. Frequency and crossover analysis are executed in multi-dimensions by time period, topic, author, research level, data, and methodology by complete enumeration of every published paper for 40 years in APJSB which included core terms of entrepreneurship in its title, abstract, or keywords. From objective and quantitative schematization of research trends and characteristics of entrepreneurship studies, novel improvement plans which are highly applicable in research fields are suggested such as diversification of studies from ecosystem perspective, identification of authors, and standardized system of extended abstract of research papers. Implications and suggestions derived from the results propose future research directions and tasks when entrepreneurship studies have been rapidly increased. Furthermore, the innovation plans of management system of journals and papers are expected to contribute promotion of entire studies by significantly reducing trial and error, and inefficiency in research process.

• Journal of Korean Biological Nursing Science
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• v.13 no.2
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• pp.81-93
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• 2011

Purpose: This study was conducted to analyze the articles published in the Journal of Korean Biological Nursing Science from 1999 when it began to 2010. Methods: One hundred seventy eight articles were reviewed using analysis criteria developed by the researchers. Results: Thirty-one percent of the research was supported financially. The most used key concepts were in the health and environment domain. For study design, experimental studies were 50.56%, especially quasi-experimental design was most frequently used (22.47%). Selection of subjects by convenience sampling was most frequent (82.58%). The major subjects of study were adult patients (25.68%). Forty-eight percent of the research had verbal consent and 11% had written consent from the participants. Exercise was common intervention (27.87%) in experimental studies. Physiologic indicators (31.65%), cognitive indicator (25.38%), psychosocial indicator (13.21%) and physical indicator (7.31%) were frequently used as a measurement tool. For data analysis, descriptive statistics (28.99%), t-test (15.06%), chi-square test (11.69%) and ANOVA (9.89%) were most frequently used. Conclusion: The number of research papers published in the Journal of Korean Biological Nursing Science has increased. Research topics varied and were mostly conducted on the basis of logical positivism. Further research should be more empirical enough to be utilized in an actual nursing care context.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.481-492
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• 2007

In this paper, a method for automatic indexing of contents to reduce effort for inputting paper information and constructing index is considered. Existing document analysis methods can't analyse various table of contents of journal paper formats efficiently because they have many exceptions. In this paper, various contents formats for journals, which have different features from those for general documents, are analysed and described. The principal elements that we want to represent are titles, authors, and pages for each papers. Thus, the three principal elements are modeled according to the order of their arrangement, and their features are extracted. And a table of content recognition system of journal is implemented, based on the proposed modeling method. The accuracy of exact extraction ratio of 91.5% on title, author, and page type on 660 published papers of various journals is obtained.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.117-135
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• 2019

Data journals and data papers have grown and considered an important scholarly practice in the paradigm of open science in the context of data sharing and data reuse. This study investigates a total of 713 data papers published in Scientific Data in terms of author, citation, and subject areas. The findings of the study show that the subject areas of core authors are found as the areas of Biotechnology and Physics. An average number of co-authors is 12 and the patterns of co-authorship are recognized as several closed sub-networks. In terms of citation status, the subject areas of cited publications are highly similar to the areas of data paper authors. However, the citation analysis indicates that there are considerable citations on the journals specialized on methodology. The network with authors' keywords identifies more detailed areas such as marine ecology, cancer, genome, database, and temperature. This result indicates that biology oriented-subjects are primary areas in the journal although Scientific Data is categorized in multidisciplinary science in Web of Science database.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.148-154
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• 2019

The purpose of this study is to review systematically the literatures on the research of the elderly speech signal processing based on the domestic gender innovation and to introduce the utility and innovation of the gender analysis methods. From 2000 to present, among the 37 research papers published in the Korean Journal, 25 papers were selected according to the inclusion and exclusion criteria. And gender analysis methods were applied to gender research subject and design. Research results show diversity of research field and high gender recognition of R & D team are needed in research and development of engineering of gender innovation perspective. In addition, government-level regulation and research funding should be systematically applied to gender innovation research processes in the elderly voice signal processing and various gender innovation projects. In the future gender innovation in the elderly speech signal processing can contribute to the creation of a new market by developing a voice recognition system and service that reflects the needs of both men and women.