• East Asian mathematical journal
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• v.35 no.4
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• pp.489-508
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• 2019

In this paper we used text mining method to analyze journals of mathematics education posterior to the year of 2016. To figure out trends of mathematics education research. we analyzed the key words largely mentioned in the recent mathematics education journals by Term Frequency and Term Frequency-Inverse Document Frequency method. We also looked at how these keywords match up with the key words that appear of education to prepare for future society. This result can infer the characteristics of mathematics education research in the aspect upcoming research topics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.21-34
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• 2023

The purpose of this study is to examine the extent of Sustainable Development Goals (SDGs)-related research in the field of entrepreneurship globally since the adoption of the SDGs at the UN General Assembly, and to compare international and domestic research trends in order to determine the direction of SDGs-related research in entrepreneurship in Korea. Utilizing three databases-Web of Science (WoS), KCI, and DBpia- SDGs-related studies in entrepreneurship were extracted by employing specific search terms. After data purification, a total of 356 studies abroad and 4 studies in Korea were used for analysis. After data purification, a total of 356 international studies and 4 Korean studies were analyzed. Due to the limited number of domestic studies, the research trends were examined by conducting frequency analysis and keyword network analysis on international studies alone. Frequency analysis revealed that SDGs research in entrepreneurship primarily focused on sustainability-related terms and was conducted in conjunction with business models, innovation, entrepreneurship education, and strategies. Furthermore, yearly frequency analysis demonstrated an expansion of topics to encompass research on entrepreneurship and SDGs policies, the roles and capabilities of female entrepreneurs in SDGs implementation, energy start-ups and SDGs, directions for implementing SDGs in business schools and SDGs education, indicators for SDGs implementation and evaluation, and technologies for sustainability. The keyword network analysis identified central topics such as business, sustainability, SDGs, innovation, entrepreneurship, business models, and education, with research areas extending to entrepreneurship ecosystems, change and strategy, ethics, and climate. This study holds significance in establishing a foundation for SDGs research in entrepreneurship, which is currently an underexplored area in Korea, by presenting emerging research trends related to SDGs in entrepreneurship.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.187-194
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• 2013

Recently, there have been many trials to analyze characteristics of research trends through a structural analysis of keyword networks in various fields. However, most previous studies have mainly focused on structural analysis harbored in some static networks and there is a lack of research on changes of such networks structure with time. In this paper, we constructed annual keyword networks by using a database of papers published in the international computer engineering-field journals from 2002 through 2011, and examined the changes of them. As a result, it was shown that most keywords in a network are preserved in the network of the next year, and their degree of connectivity and the average weight of the connections were higher and smaller, respectively, than those of the keywords which are not preserved. In addition, when a keyword network shifted to one of the next year, the connections between keywords were more likely to be removed than preserved, and the average weight of the removal connections was higher than that of the preserved ones. These results imply that the keywords are not changed over time but their connections are very likely to be changed; and there is apparent differences between the preserved and removal groups of keywords/connections with respect to degree and weights of connections. All these results are consistently observed over the ten-year datasets and they can be important principles in understanding the structural changes of the keyword networks.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.456-461
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• 2006

The purpose of this study is to systematically analyze empirical studies on community facilities of apartment in Korea, to find out research streaming and understand social backgrounds. Since the last year when well-being trend was highly interesting, consumers have showed their concern about not only just interior of house but also exterior environment of their houses. This movement has evoked consumers' interests in level and sort of resident's community space. For this study, content analysis was conducted. Article of three registered academic institute published from 1986 to 2006 were units of analysis. Using keyword through library database systems, the articles were systematically selected. 20 cases were used for data analysis. For this study, content analysis was conducted.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.279-285
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• 2023

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

• Industry Promotion Research
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• v.8 no.4
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• pp.251-256
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• 2023

The purpose of this study is to find out how much research has been done on dream analysis based on S.Freud's psychoanalytic theory, and to suggest the necessity of dream research and follow-up research on dream research. The research method was based on analysis of domestic academic journals from 2019 to 2023, a study on S.Freud's dream analysis. Among them, the data were collected and organized through a keyword classification process from the Research Information Service (RISS) and the Korean Journal Citation Index (KCI). The classification categories were psychoanalysis, domestic academic journals, dream analysis, dream interpretation, dream analysis research trends, and dream research trends. In particular, psychoanalysis, dream analysis, domestic academic journals, and research trends were searched. The conclusion was drawn as follows. First, studies on research trends on dream analysis in domestic academic journals did not occupy a large proportion. Second, the ratio of research trends centered on dream analysis keywords was also significantly low. Third, the use and frequency of dream analysis was low. Fourth, research on Korean testing tools based on dream analysis is needed.

• Journal of Korean Academy of Nursing Administration
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• v.23 no.1
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• pp.101-110
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• 2017

Purpose: This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015. Methods: For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis. Results: Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism. Conclusion: The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.307-314
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• 2019

This paper was intended to identify the knowledge structure of youth-related research by looking at the research trends of research papers published in Korean Journal of Youth Studies from 2010 to 2018. Using keywords extracted from the papers, the Centrality and Cohesion analysis of the keyword network analysis of the NetMiner program were used. In the analysis of degree centrality, the "relationship" was the highest, followed by schools and youth, and high in the order of parents and violence. In the analysis of betweenness centrality, the "relationship" was also the highest, followed by youth, school, need, education, parents, children, abuse/emotion(the same level), institutions, regions, cell phones/prevention/welfare(the same level), elementary, attachment, suicide, addiction, society, violence, children, services, support, policy/teachers(the same level). According to the cohesion analysis, school life and policy, addiction, parent & peer relations, civic education & welfare support, sentiment and thinking, college, abuse & suicide were divided into a total of seven sub-topic subjects.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.225-233
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• 2017

In this paper, we collected the articles related to artificial intelligence among SCI(E) journals published by Korean authors in 'Web of Science' and conducted frequency analysis and keyword network analysis. As a result of the analysis, the artificial intelligence thesis showed an average growth of about 10% per year, but the relative ratio decreased. As time went on, we could confirm that there is a lot of practical and applied research in artificial intelligence research. Unlike the US 'National Strategy for Artificial Intelligence Research and Development,' the field of research in Korea was focused on local and technical aspects. Therefore, Korea should go beyond the theoretical and technical iterations of artificial intelligence, and research should be carried out to present a comprehensive future direction.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.141-146
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• 2018

The authors' author keywords are the most important elements that characterize the contents of the paper, By analyzing this in real time and providing it to users, It is possible to grasp research trends. Unstructured data of a journal created in a paper is constructed as a database, make use of this to make index data structure that can search in real time. In the index data structure, a thesis containing a specific keyword is searched, By extracting and clustering the author keywords, By presenting to the user a word cloud that can be displayed by size according to the weight, designed a method to visualize research trends. We also present the results of the research trend analysis of the keywords "virus" and "iris recognition" in the implemented system.