• Journal of Digital Convergence
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• v.16 no.11
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• pp.149-157
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• 2018

The purpose of this study is to identify the tendency of media reports on the dementia management policy in Korea and to suggest policy implications such as prevention of dementia, improvement of awareness, and management of dementia through network analysis. We analyzed the linkage structure between the main texts centered on the number of citations of the main language related to the dementia management policy and the centrality and mediation as the research procedures and methods. As a result of the analysis, first, a 'micro' perspective is needed to explain practically. Second, it is desirable to understand the dementia management policy in the context of community. Third, the network structure of key words such as 'dementia management policy' suggests the possibility of research study in academic research in future research. Therefore, the phenomenon of dementia management policy will contribute to the direction of future dementia management policy, not local or temporary.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.47-55
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• 2019

The army of republic of korea have been continued to transform their logistics support system structure for better efficient logistics support system in preparation for the future environment. Logistics system has supply network structure which is connected by various units and supply network structure received attention as a factor of success of supply network. Many researchers have continuously researched inventory management, transportation or economy factors for supply network, but such a study on the one in military supply network structure analysis is still slower than the study of analysis of other factors until now. In this study, we identify military supply network structure influence factor by application of social network analysis method which is used broadly and analyze co-relationships between supply network structure influence factor and valued APL(average path length) as a criteria of efficiency of military supply network. By this study it has value of military supply network influence factor identification for the better military supply network fabrication.

• The Southeast Asian review
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• v.28 no.1
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• pp.83-120
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• 2018

For Singapore, 2017 was an uneasy year. The presidential election was fraught with controversy since the revised Presidential Election Act allowed only one candidate to be eligible for the election. The bitter feud between Prime Minister Lee Hsien Loong and his siblings shocked many Singaporeans. Succession planning for the next top leadership is still veiled in obscurity. The anti-globalization trend and the increasing pressure to raise the tax have become major challenges for Singapore's economy to overcome. China's continuous diplomatic pressure has called into the question Singapore's pragmatic foreign policy. Although its relations with China were back to normal, Singapore, the ASEAN chair in 2018, is still facing intractable problems in safeguarding ASEAN centrality in the growing US-China rivalry. In the meantime, Singapore has pursued its diversity and equality, heading toward a more matured multi-racial and multi-cultural society in 2017. The first female president, Halimah Yacob, served as a symbolic epitome of Singapore's emphasis on diversity and harmony among different ethnic groups and minorities. This great milestone, however, has largely been questioned by Singaporeans, as it seemed to be a political gesture that only utilized Halimah's double minority in the level of ideologies. The election of the Malay president has led Singaporeans to think about the real equity and equality among minorities, while strongly motivated to move toward a more inclusive society. In 2018, Singaporean leaders will try to resolve many challenging problems by reaffirming leadership succession planning, which is expected to lead Singapore to pursue a more integrated society.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.89-108
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• 2022

The purpose of this study is to reveal the specific current and future shapes of the collaborative network among organizations witch cope the COVID-19 in Korea. For this, this study conducted social network analysis, based on the response data of 73 experts from 36 COVID-19-related organizations. As a result of the analysis, it was confirmed that the Korea Disease Control and Prevention Agency (KDCA) plays a pivotal role as a control tower in coping COVID-19 in all of the analysis of degree, betweenness, and closeness centrality. In addition, the results revealed concrete forms of collaborative relationships among participating organizations in the public and private sectors that constitute the present and future networks centered on the KDCA. Furthermore, this study presented which organizations and relationships should be the focus of establishing a future collaborative network through comparative analysis between the current cooperative network and the network to be built in the future. The analysis results and discussions of this study are expected to be used as useful information for policy development related to collaborative networks that can effectively respond to disasters caused by new diseases in the future.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.172-178
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• 2022

Objectives : Although subclinical depression symptoms are associated with suicidal idea, most research have focused on clinical depression such as major depressive disorder or dysthymia. The aim of this study is to investigate network structure of depressive symptom and to reveal which symptoms are associated with suicidal ideation. Methods : We used part of data from the seventh Korea National Health and Nutrition Examination Survey. Participants were between 19 and 65 years of age (N=8,741). Network analysis with Isingfit model is used to reveal network structure of depressive symptoms and most central symptom and edges assessed by patient health questionnaire (PHQ-9). Results : The most two central symptoms were psychomotor activity and suicidal ideation. The strongest edge was psychomotor activity-suicidal ideation. Suicidal ideation also has strong association with depressive mood and worthlessness. Conclusions : These results suggest that psychomotor activity and suicidal ideation can serve as treatment target for subclinical depression and psychomotor activity, worthlessness and depressed mood may be important factor for early intervention of suicidal ideation.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.31-48
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• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.285-298
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• 2022

This study is to investigate the effects and characteristics of science and engineering integrated lessons on elementary students' creative engineering problem solving propensity (CEPSP). The science and engineering integrated lessons used in this study was a 10 lesson-hours STEM program, co-developed by University of Minnesota and Purdue University. The program was implemented in the 6th grade science class of H Elementary School located in P Metropolitan city. The main data of this study are the pre-post CEPSP result and interview with 5 students collected before and after the research. The CEPSP result was analyzed by a paired-sample t-test and hierarchical cluster analysis. As a result of the t-test, it was found that overall, the program has a positive effect on the students' CEPSP score. As a result of cluster analysis, it was confirmed that studnets' CEPSP could be classified into two groups (lower and higher score cluster). Five students whose, CEPSP score has significantly improved after the lessons were interviewed to find out what the characteristics of the program that contribute the significant change are. As a result of conducting centroid analysis of the interview transcription and the hybrid analysis method, it was found that the meaningful experiences that the five students commonly shared were 'problem solving through collaboration' and 'through repeated experiments (redesign)', problem solving' and 'utilization of scientific knowledge'. As minor reactions, 'choice of the best experimental method' and 'difference between science and engineering' appeared.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.311-320
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• 2023

This paper analyzes viewers' perception of investigative journalism before and after COVID-19, and examines the direction of investigative journalism using big data. Based on the previous research set as a social science model, the relationship between words related to big data TV current affairs programs and investigative journalism in this paper was investigated before and after the appearance of COVID-19. We visualized changes in viewers' perception of investigative journalism by analyzing text data obtained through the use of Textom, with TV current affairs programs and investigative journalism as keywords. Data was collected from 2017 to June 2022 and refined for analysis. We visualized connectivity centrality using Ucinet 6.0 and Netdraw, and clustered the number of keywords and their frequency using Concor analysis. Our study found a clear change in viewer perception before and after the pandemic. As an implication of this thesis, big data analysis was conducted with the investigative journalism as the main keyword, and the direction of the investigative journalism was presented based on the analysis. Furthermore, based on previous research, we suggest effective approaches for investigative journalism after the pandemic to better engage viewers.