• Title/Summary/Keyword: connection centrality

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Analysis of Transaction Networks among Korean IT Corporations in Nine Metropolitan Regions: Assessing Connection Strengths and Developing a Node Centrality Composite Indicator (국내 IT 기업 대상 9개 광역권 지역의 거래 네트워크 분석: 연결강도 분석 및 노드 중심성 복합지표 개발)

  • Geon Jae Yu;Hyun Sang Lee;Choong Kwon Lee
    • Smart Media Journal
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    • v.13 no.2
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    • pp.108-121
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    • 2024
  • In the IT industry, the complexity and volatility of corporate networks are gradually evolving, and concurrently, the significance of corporate networks is increasing. Previous research has employed network analysis to scrutinize inter-corporate trade relationships for strategic and policy making. However, previous studies focused on the overall network structure from a macroscopic perspective, presenting limitations in applicability at the individual IT corporation level. This study develops a novel research model incorporating sector and region-level network analysis based on connection strength, along with the derivation of a composite node centrality indicator. Using this methodology, we analyzed corporate networks across nine metropolitan areas using IT corporate transaction data. The results means that cities with a manufacturing base, such as Incheon, Busan, and Daegu, have recently established cooperative networks with IT companies. We also found that in the IT industry in Gwangju and Daejeon, certain companies dominate the transaction network.

A Study on the Research Trend of Elementary Environmental Education through an Analysis of the Network of Author Keywords (저자 키워드 네트워크 분석을 통한 초등 환경교육의 연구 동향 탐색)

  • Kim, Dong-Ryeul
    • Journal of Korean Elementary Science Education
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    • v.36 no.2
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    • pp.113-128
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    • 2017
  • This study aims to investigate the research trend of elementary environmental education. Thus, author keywords were extracted from a total of 197 academic these related to elementary environmental education during two different periods when detailed goals were applied to the 2007 and 2009 revised curriculums respectively, and then this study analyzed the network of author keywords. The results of this study can be summarized as below. Firstly, as a result of analyzing the frequency of author keywords from academic theses related to elementary environmental education, this study discovered 369 author keywords from the period when detailed goals were applied to 2009 revised curriculum. Out of them, it was found that the keyword, 'climate change education', showed the highest frequency, followed by 'environmental literacy' and 'environmental perception', except such central keywords as 'environmental education' and 'elementary school student'. From the period when detailed goals were applied to the 2007 revised curriculum, a total of 394 author keywords were discovered, and the keyword, 'environmental literacy', showed the highest frequency, followed by 'environmental perception' and 'ESD (education for sustainable development)'. Secondly, as a result of analyzing the network of author keywords, this study found out that in the total number of network connections, average connection degree, density and clique, the period when detailed goals were applied to the 2007 revised curriculum was somewhat higher than the period when detailed goals were applied to the 2009 revised curriculum. As a result of analyzing the centrality of author keywords, this study found out that during both the periods, 'environmental perception' and 'environmental literacy' were high in degree centrality and betweenness centrality, except such central keywords as 'environmental education' and 'elementary school student'. As a result of analyzing the components of author keywords as sub-networks, this study discovered 9 components from the period when detailed goals were applied to the 2009 revised curriculum and 6 components from the period when detailed goals were applied to the 2007 revised curriculum. During both the periods, the largest component was composed of keywords high in degree centrality and betweenness centrality.

The Influence of Small World and Centrality on the Paper Achievement of Government-Funded Research Institutes (과학기술계 정부출연연구기관의 논문 성과에 좁은 세상 구조와 중심성이 미치는 영향)

  • Lee, Hyekyung;Kim, Somin;Kim, Jeongheum
    • Journal of Technology Innovation
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    • v.29 no.1
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    • pp.39-73
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    • 2021
  • The cooperative network structure influences the academic performance of the research institute. In particular, South Korea's Government-Funded Research Institutes(GRI) need to establish an efficient cooperative system as a leading national R&D implementer. This study applied the Small World structure, which has been discussed as an efficient network structure, and the centrality of representing the characteristics of nodes to the cooperative network of GRI in Korea. Based on the SCIE published data from 2010 to 2019, we analyze how the Small World characteristics and centrality of GRI contribute to academic performance using a network analysis and Feasible GLS regression. The GRI cooperative network has shown that the Small World network structure facilitates the academic performance. In addition, centrality indicating the degree of direct connection showed positive significance, but centrality indicating the degree of intermediary was not significant or negative. The results of this study explain that the higher the number of institutions that exchange and cooperate, the higher the academic performance, and the higher the performance of the institutions that serve as the center of cooperation. In addition, it was established that the stronger the cooperative network of GRIs have the characteristics of Small World, the more effective it is to create research results. This study applies centrality and Small World previously discussed as an efficient network structure to the GRI cooperation network and provide implications for establishing policies and strategies related to R&D cooperation among GRIs.

Network Analysis of Herbs that are Frequently Prescribed for Osteoporosis with a Focus on Oasis Platform Research (골다공증 다빈도 처방과 구성 약물의 네트워크 분석 - 오아시스 검색을 중심으로)

  • Shin, Seon-mi;Ko, Heung
    • The Journal of Internal Korean Medicine
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    • v.42 no.4
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    • pp.628-644
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    • 2021
  • Objectives: This study analyzed, through network analysis and data mining analysis, the relationship between herbs used in osteoporosis prescriptions, diversified the analysis of osteoporosis-related prescriptions, and analyzed the combination of herbs used in osteoporosis-related prescriptions. Methods: The prescriptions used in osteoporosis treatment and experiments were established by conducting a full survey of the papers published by the OASIS site. A database for osteoporosis-related prescriptions was established, herbs were extracted, and the frequency of frequent herbs and prescriptions were investigated using Excel (MS offices ver. 2013). Using the freeware R version 4.0.3 (2020-10-10), igraph, and arules package, network analysis was performed in the first second of prescription composition. Results: Among the osteoporosis-related prescriptions, the most studied prescriptions are as follows.: Yukmijihwang-tang (六味地黃湯) and Samul-tang (四物湯). In the osteoporosis prescription network, herbs with connection centrality, proximity centrality, mediation centrality, and eigenvector centrality appeared in the order of Rehmanniae Radix Preparata, Angelicae Gigantis Radix, Poria Sclerotium, Paeoniae Radix, and Glycyrrhizae Radix et Rhizoma. After extracting the herbal combination network, including the corresponding herbs, and clustering it, it can be divided into drugs of the Yukmijihwang-tang (六味地黃湯) series and the Samul-tang (四物湯). Conclusions: This study could assist researchers in diversifyingy formula analysis in future studies. Moreover, the herbal combination used in osteoporosis prescriptions could be used to search for osteoporosis prescriptions in other databases or to create a new prescription.

Curriculum Relevance Analysis of Physics Book Report Text Using Topic Modeling (토픽모델링을 활용한 물리학 독서감상문 텍스트의 교육과정 연계성 분석)

  • Lim, Jeong-Hoon
    • Journal of Korean Library and Information Science Society
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    • v.53 no.2
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    • pp.333-353
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    • 2022
  • This study analyzed the relevance of the curriculum by applying topic modeling to book reports written as content area reading activities in the 'physics' class. In order to carry out the research, 332 physics book reports were collected to analyze the relevance among keywords and topics were extracted using STM. The result of the analysis showed that the main keywords of the physics book reports were 'thought', 'content', 'explain', 'theory', 'person', 'understanding'. To examine the influence and connection relationship of the derived keywords, the study presented degree centrality, between centrality, and eigenvetor centrality. As a result of the topic modeling analysis, eleven topics related to the physics curriculum were extracted, and the curriculum linkage could be drawn in three subjects (Physics I, Physics II, Science History), and six areas (force and motion, modern physics, wave, heat and energy, Western science history, and What is science). The analyzed results can be used as evidence for a more systematic implementation of content area reading activities which reflect the subject characteristics in the future.

Research Trends of Studies Related to the Geological Fieldwork Using Semantic Network Analysis: Focused on the Last 21 Years(2000-2020) (언어 네트워크를 이용한 야외지질답사 관련 연구 동향 분석: 최근 21년(2000~2020년)을 중심으로)

  • Jeong, Dong-Gwon
    • Journal of the Korean Society of Earth Science Education
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    • v.14 no.2
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    • pp.173-192
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    • 2021
  • The purpose of this study is to analyze the previous research on geological fieldwork from 2000 to 2020, examine the tasks that have been focused on, and suggest directions and implications for future geological fieldwork research. The data was conducted for the thesis searched on ScienceON and RISS in relation to geological fieldwork and journals listed in the Korean Citation Index(KCI), and the study title was analyzed using the semantic network analysis. For analysis, the data that had been pre-processed was visualized as a network by semantic network analysis, and frequency and centrality were analyzed. The centrality analysis was based on degree centrality and eigenvector centrality, and all analyzes were performed by dividing the entire study period into four periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. As a result, research on geological fieldwork focused more on the development of geological field courses, and in particular, jeju island was actively discussed as a learning site. Also, the study was conducted on students rather than teachers, and among them, high school students showed high frequency and centrality. In addition, it can be seen that studies on the educational effect of geological fieldwork were discussed, either in connection with programs such as STEAM, free-semester program, or indirect geological fieldwork methods such as web, flash panorama, and 3D. This study is meaningful in that it suggests the direction of future research by looking back on the research on geological fieldwork that has been done so far.

Smart Store in Smart City: The Development of Smart Trade Area Analysis System Based on Consumer Sentiments (Smart Store in Smart City: 소비자 감성기반 상권분석 시스템 개발)

  • Yoo, In-Jin;Seo, Bong-Goon;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.25-52
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    • 2018
  • This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

A Study on the Smart Tourism Awareness through Bigdata Analysis

  • LEE, Song-Yi;LEE, Hwan-Soo
    • The Journal of Industrial Distribution & Business
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    • v.11 no.5
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    • pp.45-52
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    • 2020
  • Purpose: In the 4th industrial revolution, services that incorporate various smart technologies in the tourism sector have begun to gain popularity. Accordingly, academic discussions on smart tourism have also started to become active in various fields. Despite recent research, the definition of smart tourism is still ambiguous, and it is not easy to differentiate its scope or characteristics from traditional tourism concepts. Thus, this study aims to analyze the perception of smart tourism exposed online to identify the current point of smart tourism in Korea and present the research direction for conceptualizing smart tourism suitable for the domestic situation. Research design, data, and methodology: This study analyzes the perception of smart tourism exposed online based on 20,198 news data from portal sites over the past six years. Data on words used with smart tourism were collected from the leading portal sites Naver, Daum, and Google. Text mining techniques were applied to identify the social awareness status of smart tourism. Network analysis was used to visualize the results between words related to smart tourism, and CONCOR analysis was conducted to derive clusters formed by words having similarity. Results: As a result of keyword analysis, the frequency of words related to the development and construction of smart tourism areas was high. The analysis of the centrality of the connection between words showed that the frequency of keywords was similar, and that the words "smartphones" and "China" had relatively high connection centrality. The results of network analysis and CONCOR indicated that words were formed into eight groups including related technologies, promotion, globalization, service introduction, innovation, regional society, activation, and utilization guide. The overall results of data analysis showed that the development of smart tourism cities was a noticeable issue. Conclusions: This study is meaningful in that it clearly reflects the differences in the perception of smart tourism between online and research trends despite various efforts to develop smart tourism in Korea. In addition, this study highlights the need to understand smart tourism concepts and enhance academic discussions. It is expected that such academic discussions will contribute to improving the competitiveness of smart tourism research in Korea.

Co-author Network Analysis of Research Institutes in the Computer Field Based on the Journal Articles Published in Korea (한국 학술지 기반 컴퓨터분야 연구기관 공저 네트워크 분석)

  • Kim, Byungkyu;You, Beon-Jong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.117-122
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    • 2021
  • In order to reveal the co-research relationship with key research institutes in the computer field in Korea, which have high competitiveness in the ICT field, this paper analyzes the co-author network of research institutes based on the papers of Korean journals. For this study, 15 computer journals published in Korea were selected and collected for the past 5 years. In addition, authors, affiliated institutions, and country information were extracted from the papers, and experimental data were produced using institutional identification data and SNA analysis techniques. Through this, statistical analysis was performed on researchers, research institutes, and countries, and the centrality of research institutes was measured through co-authored network analysis and visualized as a map. The results of the research that analyzed the co-author relationship based on the papers in computer science journals published in Korea are as follows. First, the status of co-author relations among researchers was statistically analyzed in detail. The number of authors, the number of co-authors, and statistics by co-authoring countries, as well as the ratio of co-authored research by institution and the ratio of co-authored by country were revealed. The co-authoring status of papers in English journals was analyzed separately to compare and analyze characteristics. Second, the centrality of each individual was measured through the co-authored network analysis of the identified researchers, institutions and countries affiliated with the institution, and the frequency of connection between data by level was identified. In addition, the co-authorization network between research institutes was visualized and presented as a map so that the overall view of the co-authoring network was presented, and the connection frequency between the institutes was checked. It is possible to recommend a research partner based on the co-authoring behavior of Korean computer researchers and the co-authoring relationship between major research institutes. For this, additional research is needed to analyze the subject areas of each institution.

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Study on Visualization of Multi-domain Network Topology (멀티 도메인 네트워크 토폴로지 시각화 연구)

  • Beom-Hwan Chang
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.169-178
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    • 2022
  • In general, organizations operating multi-domain networks find it difficult to represent and manage multiple domain net works on a single screen space. Instead, most of them are managed with multiple screens visualizing network topology by domain or partitioning one screen area into multiple domains. We propose an efficient method to visualize the topology using only minimal connection information between domain-agnostic nodes in this work. This method visualizes the topology by utilizing centrality indices representing the influence of nodes in the network. Furthermore, the method dynamically segments the entire node's display area using virtual Root nodes to auto-separate domains and weights of child nodes and placing nodes in 3D space. Thus, although it is a straightforward method, the multi-domain network topology can be visualized with only minimal connection information between nodes.