• Title/Summary/Keyword: In-degree Centrality

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Features of Science Classes in Science Core Schools Identified through Semantic Network Analysis (언어네트워크분석을 통해 본 과학중점학교 과학수업의 특징)

  • Kim, Jinhee;Na, Jiyeon;Song, Jinwoong
    • Journal of The Korean Association For Science Education
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    • v.38 no.4
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    • pp.565-574
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    • 2018
  • The purpose of this study is to investigate the features of science classes of Science Core Schools (SCSs) perceived by students. 654 students from 14 SCSs were surveyed with two open-ended questions on the features of science classes. The students' responses were analyzed with NetMiner 4.5, in terms of the centrality (of betweenness and of degree) analysis and the community analysis. The results of the research are as follows: (1) the science classes of SCSs were perceived by students to be of the environment of free questioning, active participation and communication, caring teacher, more science experiments and advanced contents, and knowledge sharing; (2) science classes in SCSs were perceived to be different from those of ordinary high schools because SCSs provide more opportunities for science-related special courses (like project work, advanced science subjects), extra-curricular activities, inquiry and research activities, school supports, hard-working classroom environment, longer studying hours, R&E and club activities. The students' perceptions of SCS science classes appear to be in line with the characteristics of 'good' science lessons from previous studies. The SCS project itself and the features of SCS science classes would help us to see how we introduce educational innovations into actual schools.

A Network Analysis of Information Exchange using Social Media in ICT Exhibition (ICT전시회에서 소셜 미디어를 활용한 정보교환 네트워크 분석)

  • Ha, Ki Mok;Moon, Hyun Sil;Choi, Il Young;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.1-17
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    • 2014
  • The proliferation of using social media and social networking services affects the lifestyles of people. These phenomena are useful to companies that wish to promote and advertise new products or services through these social media; these social media venues also come with large amounts of user data. However, studies that analyze the data of social media within the perspective of information exchanges are hard to find. Much of the previous research in this area is focused on measuring the performance of exhibitions using general statistical approaches and piecemeal measures. Therefore, in this study, we want to analyze the characteristics of information exchanges in social media by using Twitter data sets, which are relating to the Mobile World Congress (MWC). Using this methodology provides exhibition organizers and exhibitors to objectively estimate the effect of social media, and establish strategies with social media use. Through a user network analysis, we additionally found that social attributes are as important as the popular attribute regarding the sustainability of information exchanges. Consequently, this research provides a network analysis using the data derived from the use of social media to communicate information regarding the MWC exhibition, and reveals the significance of social attributes such as the degree and the betweenness centrality regarding the sustainability of information exchanges.

Differences in Environmental Behavior Practice Experience according to the Level of Environmental Literacy Factors (환경소양 요인별 수준에 따른 환경행동 실천 경험의 차이)

  • Yoonkyung Kim;Jihoon Kang;Dongyoung Lee
    • Journal of the Korean Society of Earth Science Education
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    • v.16 no.1
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    • pp.153-165
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    • 2023
  • This study investigates learners' environmental literacy, classifies the results by factors of environmental literacy, and then investigates the differences in the students' environmental behavior practice experiences according to the classification by factor. The study was conducted with 47 6th grade students from D elementary school located in P metropolitan city as the subject of final analysis, and environmental literacy questionnaires and environmental behavior practice experience questionnaires were used as the main data. As a result of the study, the learners were classified into three groups according to the factors of environmental literacy, and they were respectively named as the "High environmental literacy group", "low environmental literacy group", and "Low Function and Affectif group". A Word network was formed using the descriptions of environmental behavior practice experiences for each cluster, and a Degree Centrality Analysis was performed to visualize and then analyze. As a result of the analysis, "High environmental literacy group" was confirmed, 1) recognized the subjects of environmental action practice as individuals and families, 2) described his experience of environmental action practice in relation to all elements of environmental literacy, and had a relatively pessimistic view. "low environmental literacy group", and "Low Function and Affectif group" were confirmed 1) perceive the subject of environmental behavior practice as a relatively social problem, 2) the description of the experience of environmental behavior practice is relatively biased specific factors, and the "Low Function and Affectif group" is particularly focused on the knowledge element. And 3) it was confirmed that they were aware of climate change from a relatively optimistic perspective. Based on this conclusion, suggestions were made from the perspective of environmental education.

Patent Application Research Analysis on Domestic Smart Factory Technology Through SNA (SNA를 통한 국내 스마트공장 기술에 관한 특허 출원 조사 분석)

  • Jae-Hyo Hwang;Ki-Jung Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.267-274
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    • 2024
  • In this paper, we investigated the number of domestic patent applications by year, the number of domestic patent disclosures by year, and the number of domestic registrations by year regarding smart factories. The number of patent applications by applicant type was investigated. Based on the patents studied, it was found that the IPC appearing in the most patents was G05B 19/418. In addition, through social network analysis of smart factory patented IPCs, it was found that G05B 19/418 was the IPC with the highest degree of centrality. From the above, if the IPC of the core technology of the patent submitted for smart factory is G05B 19/418, the technology combined with G05B 23/02, that is, the technology combining "factory control" and "monitoring" is the most patented. When the IPC of the core technology was G06Q 50/04, it was confirmed that the technology combined with G06Q 50/10, that is, the technology combining "manufacturing" and "service" was the most applied for patents. Through this, it was found that in order to apply for a patent for a smart factory, it would be necessary to file a patent application that takes into account the connectivity between IPCs.

Analyzing the relationship between employee characteristics and performance in call center organizations: integration of social network analysis and repertory grid technique (조직 내 사회적 특성과 개인적 특성이 콜센터 업무 성과에 미치는 영향 분석: 사회연결망과 RGT를 중심으로 한 A사 사례 연구)

  • Kim, Jongmyoung;Geum, Youngjung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.5
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    • pp.466-475
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    • 2020
  • Current performance evaluation of call center employees is dependent on the number of calls they have resolved, regardless of the individual and social characteristics of employees. However, since call center tasks are highly customer-oriented and emotional laborious, individual capability as well as social characteristics of employees is critical to performance. Therefore, this study analyzed the relationship between employees' individual/social characteristics and their performance. To extract individual characteristics, a repertory grid technique was employed, whereas social network analysis was conducted to extract the social characteristics of employees. Using individual and social characteristics as input variables, multiple regression was conducted to analyze the effect of each variable on performance. As a result, in-degree centrality of dining network, initiative characteristics, open characteristics, and enjoyment of studying were determined to be important variables for performance. This study is expected to be used in both performance management and human resource management of call center practices.

Social awareness of Arduino and artificial intelligence using big data analysis

  • Eun-Sang, Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.189-199
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    • 2023
  • This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.

Characteristics of Science-Engineering Integrated Lessons Contributed to the Improvement of Creative Engineering Problems Solving Propensity (창의공학적 문제해결성향에 기여한 과학-공학 융합수업의 특성)

  • Lee, Dongyoung;Nam, Younkyeong
    • 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.

Comparative Analysis of Citation Patterns between Journals and Conferences: A Case Study Based on the JKIISC

  • Byungkyu Kim;Min-Woo Park;Beom-Jong You;Jun Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.8
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    • pp.171-190
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    • 2024
  • This paper conducts a comparative analysis of citation patterns between journals and conferences using bibliometric and social network analysis on references from the 'Journal of the Korea Institute of Information Security and Cryptology (JKIISC)'. The results indicate that conference references slightly exceed journal references, with around 80% being international publications, highlighting Korean researchers' high dependency on overseas publications. Analysis of citation age shows trends of increasing immediacy citation rate, lengthening citing half-life, and shortening peak time, with domestic publications having higher immediacy citation rate and international publications having slower citing half-life. Mapping SCOPUS journals and ICORE conferences revealed that journal citations mainly come from 'Computer science' (32.3%), 'Engineering' (23.5%), 'Mathematics' (16.7%), and 'Social Cciences' (12.8%), along with other research fields (25.6%), while conference citations are predominantly in 'Cybersecurity and Privacy' with recent increases in 'Computer Vision and Multimedia Computation' and 'Machine Learning'. Co-citation network analysis shows higher degree centrality for conference groups and international publications. The co-citation frequency between different types of literature was highest between journals and conferences (36.9%), compared to within journals (34.3%) or within conferences (28.8%). Lastly, network visualization maps are presented to explore the structural connections among co-cited publications and their research fields. The results of this study suggest that the field of information security research in Korea effectively balances the use of journal and conference literature, indicating that the field is developing through a complementary relationship between these sources.

Network Analysis of Epilepsy Formulas from Ministry of Food and Drug Safety's 9 Herbal Manuscripts (식약처 고시 9종 한약서에 수록된 뇌전증 치료 한약 처방의 네트워크 분석)

  • Kim Tae Hwan;Kim Hye Yeon;Han Ju Hui;Bang Mi Ran;Chang Gyu Tae;Lee Jin Yong;Kim Hyo In;Lee Donghun;Lee Sun Haeng
    • The Journal of Pediatrics of Korean Medicine
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    • v.38 no.3
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    • pp.53-65
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    • 2024
  • Objectives This study aimed to analyze herbal formulas for epilepsy recorded in nine herbal manuscripts regulated by the Ministry of Food and Drug Safety (MFDS). The goal was to identify the frequency and associations of the included herbs and to determine effective herbal combinations for epilepsy treatment. Methods The study analyzed formulas for epilepsy (癲癎) from nine herbal manuscripts regulated by the MFDS: 東醫寶鑑, 方藥合編, 鄕藥集成方, 景岳全書, 醫學入門, 濟衆新編, 廣濟秘笈, 東醫壽世保元, and 本草綱目. We examined the frequency of herbs, herb pairs, and their degree centrality within the network using Netminer 4.5. Results The analysis identified 143 different herbs across the 159 formulas. Frequently included herbs were 朱砂, 人蔘, 天南星, 麝香, 茯笭. The most common herb pairs included 朱砂-麝香, 茯笭-人蔘, 朱砂-天南星, 朱砂-人蔘, 朱砂-遠志, 半夏-天南星. Network analysis revealed four distinct clusters: Group 1 (tranquillizing by heavy settling and opening the orifices), Group 2 (dispelling phlegm and regulating qi), Group 3 (tonifying and tranquillizing), and Group 4 (pacifying the liver and extinguishing wind). Conclusion The herbal formulas for epilepsy in the nine MFDS-regulated manuscripts have antiepileptic effects through central nervous system sedation and neuroprotective actions.

A Study on the Relationship between Cooperation Network and Publication Performance of Korean Government-Funded Research Institutes through Collaborative Paper Status (공동논문 현황을 통한 정부출연(연)의 협력네트워크 구조와 논문성과와의 관계 분석)

  • Chung, Taewon;Chung, Dongsub;Kim, JeongHeum
    • Journal of Korea Technology Innovation Society
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    • v.17 no.1
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    • pp.242-263
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    • 2014
  • Establishment of efficient cooperative ecosystem of research institutes is important for the efficiency of national innovation system, especially in the era of technology convergence. Performance of institutes inside the ecosystem is dependent on the position of the institutes in the system. This study investigates the relationship between network structure and research performance, and determines significant factors on the research performance. The results of 5 year panel data analysis of SCI journal papers of Korean government research institutes indicate that four network centralities -degree, betweenness, closeness, and eigenvector- and structural holes have significant effect on the research performance of the institutes. Among the four centralities, closeness and eigenvectors are more significant than others. Implications of the results of this study for policy of establishing efficient cooperative system are that increasing the cooperative activities of less active institutes is more effective for research performance than increasing the magnitude of cooperative activities of all institutes. Also, when an institute starts a new cooperative relationship, it is better to have relationship with an active institute first.