Earticle

This study aims at divulging basic structure and evolution mechanism of IT Industry knowledge network in Chungnam Province. In terms of methodological approaches, it analyzes formation of social network among joint research institutions, which have been initiated from Chungnam-based universities from 2005 to 2008. Major findings are as follows: First of all, even though the public organizations have strengthened major links of knowledge network, it cannot underestimate the latent force of the private sector as its participation rate is about 56.4%. Secondly, in Chungnam Province, sectors representing the upper centralities are confined to semiconductor and display. Presently, as they have been designated as brand-new growth engines by the central government, it is almost certain that their synergy effect would be expanded over time. Thirdly, compared with Chungnam-based organizations, comparatively higher participation rate comes from the Capital Region, encompassing both Seoul and Gyeonggi. In addition, the participation rate from Daejeon is almost same as that of Chungnam, explicitly indicating the fact that external, not internal, force still exerts more powerful impact. Nonetheless, judging from time-series data, internal linkages among Chungnam-based organizations have shown ever-increasing trends. In general, the overall IT Industry knowledge network in Chungnam Province has evolved from the linear patterns to the plural ones. Therefore, the-rich-get-richer and the poor-get-poorer mechanism has been ameliorated over the research period, implicitly implying that the vernacular IT network in Chungnam Province has rather randomly formulated, even without any 'tlagship' organization.

Purpose: The purpose of this study is to empirically investigate the multidimensional transformation of literacy as a core competency adapting to the digital environment in contemporary society and to propose directions for improving literacy policies and educational programs. Methodology: Using social big data collected from Naver and Daum between 2021 and 2024, the study employed text mining, network analysis, CONCOR analysis, QAP regression, and topic modeling. Key keywords were identified through word frequency and TF-IDF analysis, while N-gram analysis and network visualization were used to examine the relationships between major topics. Findings: The analysis revealed that digital literacy, media literacy, and data literacy emerged as core themes, and their networks demonstrated statistically significant structural patterns. QAP regression analysis confirmed that the literacy-related network exhibited clear patterns compared to a random network, and CONCOR analysis indicated that major topics were closely interconnected. Implication: Policy recommendations include collaborating with community stakeholders to develop localized literacy programs, enhancing digital infrastructure to reduce the information gap, and offering lifelong learning opportunities. Subsidized digital literacy workshops can help address disparities in underserved areas. Integrated approaches in policy and education are essential, with tailored programs and policy support to reduce information inequality.

본 연구는 2005년부터 2024년까지의 공학 연구의 진화를 계량서지학 및 네트워크 기반 분석 방법을 통해 탐색하였다. Web of Science 데이터베이스에서 수집한 19,994편의 논문 중 정제 과정을 거쳐 19,552편을 분석 에 활용하였다. 키워드 동시 출현 분석, 주제 군집화, 국제 협력 네트워크 분석을 위해 Biblioshiny와 Python 도구를 사용하였다. 분석 결과, 2017년 이후 연간 논문 게재 수가 약 87% 증가하였으며, 주요 연구 주제도 기존의 계산 모델 중심에서 인공지능(AI) 및 지속가능성 중심의 주제로 전환되었다. 중국, 미국, 유럽 국가들이 핵심 연구 기여국으로 나타났으며, 이 중 중국은 글로벌 협력에서 주도적인 역할을 수행하고 있는 것으로 분석되었다. 이러 한 결과는 공학 연구가 점차 학제 간 융합적이며 국제적으로 연결된 형태로 진화하고 있음을 보여준다. 본 연구는 또한 특수목적 영어(ESP: English for Specific Purposes)에 대한 시사점을 제공한다. 공학 분야의 방대한 초록 데이터를 기반으로 도출된 담화 패턴은 STEM 교육 환경에 적합한 ESP 교육과정 개발에 활용될 수 있으며, 학습 자들이 분야 특화된 소통 능력을 향상시키는 데 기여할 수 있다.

This study explores the evolution of engineering research from 2005 to 2024 using bibliometric and network-based methods. From 19,994 articles retrieved from the Web of Science, 19,552 were analyzed after refinement. Biblioshiny and Python were used for keyword co-occurrence, thematic clustering, and collaboration network analysis. Results show an approximately 87% increase in annual publication volume after 2017, with themes shifting from computational modeling to AI-driven and sustainability-focused topics. China, the U.S., and several European countries were key contributors, with China leading global collaboration. Findings reveal an increasingly interdisciplinary and internationally connected research landscape. The study also provides implications for English for Specific Purposes (ESP) by identifying evolving discourse patterns relevant to STEM education. These patterns, drawn from large-scale engineering abstracts, can inform the development of ESP curricula that reflect authentic disciplinary discourse and support learners in navigating field-specific communication.

The analytics lens of big data is very popular in both industry press and academic literature where big data is often discussed in the contexts of volume, velocity, and variety. This study offered an innovation lens of big data as digital service innovation. An evolutionary, ecosystem-based framework is adopted for digital service innovation. Digital trace data from Twitter provides the opportunity to see glimpses of big data ecosystems and the elements of big data services at two stages in the evolutionary process. Also, co-hashtag network analysis and community structure detection are used to understand the structure and dynamics of the big data ecosystem and its elements, over time. Finally, discussions and implications are presented.

In modern economy, any firm cannot sustain by itself. Whatever the type of a firm, it is tangled up with other firms in any relation of supply and demand, partnership or competition, etc. In 2021, for example, chip shortage caused by the spread of COVID-19 and the sanction on Chinese chipmakers stroke the global automotive industry. As a result, major car original equipment manufacturers (OEMs) such as GM, Ford, Toyota, and many others stopped their production, which serially stopped their automotive component supplier’s production as well. However, the business magazine Forbes warns the worse situation with the messages “Battery scarcity could dwarf chip shortage impact on global auto sales” and “The semiconductor shortage will cut a total of 8.1 million cars from global production between 2021 and 2023, while between 2022 and 2029, 18.7 million rechargeable electric cars will be lost because of battery cell shortages” (Winton 2021). Due to the interdependence between firms, if any disruption erupts in the industry, its ripple effect impacts the cross-over in a multi-tiered value chain (Cachon and Lariviere, 2001). In 2010s, electric vehicle industry emerged by strong environment regulations and the hyper growth of the industry pioneers who are strongly based on information technology (IT), such as Tesla. Actually, automotive industry including electric vehicle is no longer limited to manufacturing, but is growing rapidly through a complex value chain combined with advanced IT technologies. Therefore it is highly required to understand the complex pattern and sustainability of the highly entangled system. In this research we investigate how the electric vehicle industry emerges and the resilience of the value chain changes. To tackle the research question, we introduce the novel methodological framework based on complex network theory and agent based model approach. From the empirical data on electric vehicle value chain of 6 years, we apply the framework to address the evolution of the industry using weighted network analysis (Figure 1). We found that the electric vehicle industry becomes more heterogeneous structure (Figure 2). This means that the companies. In complex network theory, the heterogeneous network structure has been well known to have the properties of “double-edge swords” in the robustness of the system, that is, it is usually very robust, but the collapse of a few central firms can cause whole system to collapse with a huge ripple effect (Albert et al. 2000). With the understandings of structural properties of electric vehicle value chain network, we examine the resilience of the network with introducing the agent based simulation model. From our simulation results, as year goes, the electric vehicle value chain becomes less resilient. Furthermore, from the result of the distinction between individual firm’s impact of unweighted and weighted aspect, we found some firm’s influence would be underestimated when one only consider the unweighted network properties. Our novel approach based on weight network analysis and agent based modeling would more capture the characteristics of electric vehicle industry and shed light on understanding systemic risks due to the individual firm’s disruption.

본 연구는 약 40년 동안의 국내 사회복지 정책 분야 연구의 흐름을 실증적인 차원에서 개괄적으로 살펴보는 데 그 목적이 있다. 이를 위해서 본 연구는 사회복지 정책 분야와 관련하여 가장인지도가 높은 다섯 개의 학술지를 선정하여 게재된 모든 논문의 정보를 수집하였다. 본 연구에서 연구 전반을 개괄하는 주요 관측 지점은 연구의 내용적 측면과 더불어 연구 협업 구조이다. 이를 위해서 논문 정보와 저자 정보를 활용하여, 전자를 통해 논문의 주요 내용을 포착하고 후자를 통해 공저자 네트워크를 추출했다. 논문 내용을 포착하기 위해서 빈출어와 핵심어(key words) 를 활용하여 공존 구조에 기반한 의미 네트워크 분석(semantic network analysis)을 활용하고, 공저자 네트워크를 통해 하위 그룹(sub-community)의 존재와 중심성(centrality)이 높은 연구자의분포를 확인하였다. 장기간에 걸친 변화를 포착하기 위해서 각 분석은 시기 구분을 통해 비교 과정을 거쳤으며, 시기 구분을 위해 논문 생산 트렌드를 기초로 절단점 분석(break point analysis) 을 수행했다. 분석 결과를 통해 논문 생산의 시기별 뚜렷한 변화와 내용적 변화, 그리고 공저자구조에서의 역동성을 발견할 수 있었다. 연구의 양적 팽창과 거대 공저자 네트워크의 형성과 주요 연구자의 연구 주제에 대한 검토를 통해 한국 사회복지정책 연구 흐름의 역사적 의의와 제약점을 통한 추후 발전을 위한 제언을 연구 말미에서 다루었다.

This study aims to provide an empirical overview of the trends in domestic research in the field of social welfare policy over approximately 40 years. The study selected the five most recognized academic journals on social welfare policy and collected information on all published papers. The main observational points for summarizing the overall research include the substantive content of the studies and the collaborative structures. This study captured the main contents of the papers and extracted co-authorship networks with the abstract and citation information of articles. This study uses frequent words and keywords to conduct semantic network analysis based on co-occurrence structures. At the same time, the presence of sub-communities and the distribution of researchers with high centrality were determined through co-authorship networks. The analysis underwent a comparative process through period differentiation, and breakpoint analysis was performed based on the trend of paper production for period segmentation. The analysis revealed apparent period-specific changes in paper production, content changes, and the dynamism within the co-authorship structure. The study concludes with suggestions for the historical significance of the Korean social welfare policy research trajectory and future developments, addressing the constraints identified through the review of the research themes of key researchers amidst the quantitative expansion of research and the formation of large co-authorship networks

한국형 SNS의 성장 가능성을 알아보기 위해 국내 1위 모바일 IM인 카카오톡 사례를 중심으로 분석해본 결과 다음의 사항들을 발견할 수 있었다. 첫째, 카카오톡은 PC상의 메신저 서비스와 다르게 모바일 IM 서비스를 바탕으로 소셜서비스 회사로 진화하고 있었다. 둘째, 카카오톡은 다양한 소셜서비스(사진기반 카카오스토리, 게임 마케팅 플랫폼 게임센터 등)를 시도하여 성공적으로 SNS 회사로 안착하였다. 셋째, 트위터의 사례처럼 플러스친구를 통한 뉴스 서비스, 아바타 및 앱스토어 등을 통해서 소셜미디어 및 소셜플랫폼 회사로 진화하고 있었다. 이런 한국시장에서 카카오톡의 성공은 NHN의 라인을 통해 일본 및 동남아시장에서 확대 재생산되고 있다. 라인은 카카오톡의 다양한 검증된 SNS 실험들을 일본시장에 적용시킴으로써 그 성공을 이어가려고 하고 있다. 온라인 웹서비스 싸이월드가 SNS로 세계시장에서 이루지 못한 것을 모바일 IM인 카카오톡, 라인은 그 성공 가능성을 한층 높여 주고 있다.

I made an analysis on the case of Kakao Talk, which is Korean top mobile instant messaging service, to find the growth potential of Korean Social Network Service in the global market. First, I found that unlike the PC messenger services, Kakao Talk is not only unlimited in mobile IM service provider but also has evolving into a social network service firm. Second, attempts with a variety of social services such as photo-based Kakao Story and Marketing Platform for Mobile Game, Kakao Talk successfully landed as a SNS company. Third, with 'Plus Friends' Service, soon-to-be launched Avatar and App Market Service, Kakao Talk is evolving into social media and social platforms. The big success of Kakao Talk in Korean market is expanding and reproducing into Japanese and Southeast Asian markets through the 'Line' serviced by NHN. Line is applying the proven success stories of Kakao Talk to the Japanese and Southeast Asian markets. It means that Kakao and Line, both are mobile IM services, have raised the possibility of success in the global SNS market although online web-based SNS Cyworld has failed in the global market.

본 연구는 텍스트 마이닝 기법을 활용하여 2000년부터 2025년까지 발표된 한국 댄스스포츠 분야의 연 구 동향을 체계적으로 분석하였다. RISS 데이터베이스에 수록된 총 152편의 학술 논문을 대상으로, TF-IDF 분석, 단어 빈도 분석, 의미 네트워크 분석 및 CONCOR(반복 상관 수렴) 군집화 기법을 결합하여 주요 연구 주제와 구조적 변화를 도출하였다. 분석 결과, 초기 연구는 주로 ‘참여 동기’, ‘심리적 특 성’ 등 개인 수준의 주제를 다루었으나, 최근에는 ‘교육 개입’, ‘노인 건강’, ‘심리 조절’ 등 사 회 지향적 주제로 확장되는 경향을 보였다. 이러한 주제 전환은 고령화, 교육 수요의 변화, 문화 정책의 진화와 같은 한국 사회의 구조적 변화와 밀접한 관련이 있다. 의미 네트워크 분석을 통해 이경숙 와 성재 형(2009)이 제안한 구조적 가설이 확인되었으며, 단순 주제 분류에서 통합적이고 상호 연결된 연구 구조 로의 진화를 보여주었다. ‘노인’, ‘교육’, ‘건강’, ‘참여’와 같은 고 중 심성 키워드는 댄스스포 츠 연구가 고령화, 정신 건강, 교육 형평성과 같은 사회적 과제와 점점 더 밀접하게 연관되고 있음을 시 사한다. 본 연구는 향후 스포츠과학, 공공보건, 사회교육 분야에서의 학제 간 연구 및 정책 수립에 실증 적 기초 자료를 제공할 수 있을 것으로 기대된다.

Objectives This study aims to examine research trends in Korean Dance Sports from 2000 to 2025, focusing on thematic developments and structural changes in response to social and policy shifts. Methods A total of 152 academic papers from the RISS database were analyzed using text mining techniques, including TF-IDF, word frequency analysis, semantic network analysis, and CONCOR clustering. Results Early studies centered on individual-level topics like participation motivation and psychological traits. More recent research has shifted to themes such as educational interventions, elderly health, and psychological well-being, reflecting Korea’s demographic and educational changes. Semantic network analysis supported Lee and Sung’s (2009) hypothesis, revealing a move toward a more integrated research structure. High-centrality keywords such as “elderly,” “education,” and “participation” highlight the field’s growing relevance to societal challenges. Conclusions The findings suggest that Dance Sports research increasingly intersects with public health, education, and aging policy. This study offers a foundation for future interdisciplinary research and evidence-based policy design.

This paper constructs interbank network based on the overnight interest rates of SHIBOR database. Direct friction and indirect friction of interbank network are defined and the influencing factors of friction are tested through panel data analysis. Results of panel regression show that four network centrality measurements of in degree, out degree, in degree and out degree all have significant effect on indirect friction, by contrast, only in degree and out degree have significant effect on direct friction. There are different effects under the condition of different samples. The results indicate that network structure determined by price spread influences the relationship between banks and frictions.

China’s traditional industry clusters meet challenges and opportunities as the global economy goes ups and downs. Following the trend of industry upgradation is a highlight in both theoretical and practical domain. This paper focuses on the principles of dynamic evolution of China’s industry clusters in order to pursuit and establish its enduring growing drive and competitive advantages. This paper gives research into dynamic evolution of cluster network, centering on its inherent relationship with the core enterprise transformation and the restructure flexibility of cluster members and defines “the transformation and up gradation of the core enterprises in cluster network”, finds out the dynamic and persistent effect of transformation and upgradation of the core enterprises on network resources and puts forward the dilemma of the dynamic evolution and upgradation of China’s cluster network.

The abstract is to be in fully-justified italicized text as it is here, below the author information. Use the word “Abstract” as the title, in 12-point Times New Roman, boldface type, centered relative to the column, initially capitalized. The abstract is to be in 11-point, single-spaced type, and may be up to 3 in. (18 picas or 7.62 cm) long. Leave two blank lines after the abstract, then begin the main text. All manuscripts must be in English.

In this paper, two-component system gene profile and metabolic network gene profile based phylogenetic trees were constructed, and two trees were compared with each other to estimate the evolutionary relation of bacterial sensing system and metabolism. Gene profiles of TCS and metabolic network suggested that bacteria employed different evolution strategies for optimization of two-component system and metabolic network. Via comparative analysis it was found that TCS based tree showed better family grouping than metabolic network based tree, and this result deduced that TCS and metabolic network have been modified following self-evolution and recruitment models, respectively. [This work was supported by the Korean Systems Biology Program from the Ministry of Education, Science and Technology through the Korea Science and Engineering Foundation (No. M10503020001-07N0302-00112)]

Enterprise organization can be thought as a complex system which constitutes of each level employees by interactions, and its robustness and fragility will affect tits survival and development directly, even its performance. This paper tries to look for the evolution characteristics of enterprise organization and constructs the model from complex network perspective by abstracting enterprise organization, then derives and calculates its robustness and fragility, and obtain the robustness threshold of enterprise organization which under the random attacks and deliberate attacks. The conclusion can be drawn through case study are as follows: the enterprise organization is a scale free network, when it reaches a certain scale, its stability depends on the number of junior staff interaction. So we can improve the robustness of enterprise organization by changing the network formation mechanism, strengthening network maintenance and create a good atmosphere of teamwork.

Synergetic neural network (SNN) is a top-down network to explain the phase transition and self-organization in non-equilibrium system. The network parameters have a crucial impact on the recognition performance of synergetic neural network. At present, there is no good way to control and adjust the network parameters. To solve these problems, an improved parameters optimization algorithm based on differential evolution algorithm is proposed and implemented in this paper. There are two main works in this paper. Firstly, a semantic analysis model based on synergetic neural network is presented. Secondly, differential evolution algorithm is used to search the global optimum of network parameters in the corresponding parameter space. The experiments showed that the optimization algorithm can improve the synergetic recognition performance.

Localization as a key problem of wireless sensor network technology, has been the subject of widespread attention. This paper presents an improved positioning algorithm of wireless sensor network based on differential evolution(DE). Firstly, the algorithm improves on each jump distance measurement method in the traditional DV-hop algorithm, thereby reducing distance estimation error between anchor nodes and the unknown nodes, and then through the DE algorithm to obtain better positioning accuracy. Simulation results show that improved positioning algorithm has improved significantly in positioning accuracy compared to the previous DE positioning algorithm and least-squares algorithm, under different error factor and the density of anchor nodes. The algorithm has features of good robustness, global search capability and the ability to inhibit the accumulation of errors, suitable for a variety of applications in wireless sensor networks localization.

디지털(digital) 기술의 발전에 의해 주도되고 있는 정보 혁명이 과거 어느 때 보다도 강력하고 빠르게 인류 역사의 흐름을 변화시키고 있음은 부인할 수 없는 사실일 것이다. 디지털 환경은 제품의 기능 및 디자인의 기대 가치에 직간접적으로 영향을 미치며 디자인 대상인 제품의 의미, 사용자와의 관계 등에 관한 재해석을 요구하고 있다.(중략)

This study examines the historic evolution of FTA network during the period from 1973 to the mid-2010s. We first observe important empirical features that have appeared in FTA network evolution over time and, then, show that these features match with micro-incentives of participating individual countries. Finally, by incorporating empirical observations and micro-incentives of countries into the macro-evolution model, we explain how the FTA network evolves over time. The macro-evolution model based on empirical observations and micro-incentives well explains the evolution of FTA network, especially until the early 2000s. This fact implies that even random formation process of network produces a good approximation to the observed network as long as important features are well incorporated into the network formation process. Additionally, we observe that although the proliferation of regionalism may not lead to complete global trade liberalization, it makes substantial contribution to the establishment of global village.

Background: This study investigated long-term publication trends and thematic evolution in the Journal of Yeungnam Medical Science (JYMS) using bibliometric and text mining approaches.Methods: Publication metadata from JYMS articles published between 1986 and 2025 were analyzed. Author keywords were preprocessed through normalization and stopword removal. Furthermore, keyword frequency analysis, word clouds, trajectory heatmaps, thematic evolution analysis, burst keyword analysis, and keyword co-occurrence network analysis were conducted using Python-based bibliometric methods.Results: A total of 1,760 articles were analyzed. The average number of keywords per article increased from 1.5±1.7 (1986?1995) to 3.8±1.4 (2016?2025). Earlier decades were characterized by keywords related to pregnancy, psychiatry, and disease-specific topics, whereas recent years demonstrated the increasing prominence of imaging-, metabolic-, and outcome-related research. Coronavirus disease 2019 emerged as the most prominent recent burst keyword. Co-occurrence network analysis demonstrated increasing interdisciplinary connectivity, with imaging-related keywords occupying central network positions.Conclusion: Over the past four decades, JYMS publications have demonstrated progressive thematic diversification and increased interdisciplinary integration. Bibliometric and text mining analyses may provide valuable information on the journal’s future research directions and academic development.

(Purpose) Recently, universities are strengthening joint research and cooperation networks to secure research competitiveness and develop win-win growth with local communities. Opportunities and capabilities for cooperation between universities tend to appear differently depending on the level of research infrastructure or administrative support conditions of each university, which is emerging as a task that needs to be solved in terms of balanced regional development. The purpose of this study is to analyze how 53 four-year universities located in the Chungcheong region form research networks through joint research over time and to derive policy implications for further activating such network activities. (Design/methodology/approach) To achieve this research objective, the study employs network theory and Social Network Analysis (SNA) to empirically analyze the annual joint research networks of universities in the Chungcheong region. Data collection was conducted using the NTIS research project information system, and the Netminer program was utilized as the network analysis tool. (Findings) The analysis results indicate that, although research collaboration has diversified, there is still a tendency for research partnerships to be concentrated around certain universities such as KAIST and Chungnam National University. (Research implications or Originality) Therefore, other universities in the Chungcheong region should actively seek collaboration with other institutions rather than conducting research independently, establish research clusters, and expand opportunities for joint research participation to enhance overall synergy.

이 글은 미국의 사이버 안보협력 네트워크가 오바마, 트럼프, 바이든 행정부를 거치면서 단(單)허브형에서 다(多)허브형을 거쳐 탈(脫)허브형으로 점차 진화해왔으며, 이는 각 행정부의 대외정책 기조를 구성하는 전략적 이해관계가 사이버 안보 담론과 관련 법제 및 정책에 영향을 미치며 비롯된 결과임을 보이고자 하였다. 즉 대외정책 기조가 각 집권기 사이버 안보에 대한 담론과 사이버 안보 관련 국내 법제 및 정책을 조정하거나 통제하는 변수로 작용하면서 결과적으로 사이버 안보협력 네트워크의 유형을 결정하였다고 주장한다. 이러한 주장을 뒷받침하고자 이 글은 먼저 네트워크 이론의 시각을 도입하여 세 행정부의 사이버 안보 전략을 분석함으로써 각 시기 미국의 전략에 내재된 사이버 안보협력 네트워크의 유형과 성격을 살펴보았다. 나아가 미국의 사이버 안보협력 네트워크가 변화하게 된 원인을 추적하기 위해 이익 (interests), 제도(institutions), 관념(ideas) 변수의 삼자 간 구성적 상호작용에 주목 하여 국가전략을 설명하는 ‘구성적 제도주의(constitutive institutionalism)’의 이론적 자원을 부분적으로 원용하였다.

This paper asserts that the US led cyber security cooperation network has gradually evolved from a ‘mono-hub’ to a ‘multi-hub’, and to a ‘hub-bypass’ through the Obama, Trump, and Biden administrations. It is argued that such transformation is due primarily to the strategic interests constituting each administration’s foreign policy which have influenced the cyber security discourse and related law and policies. In order to support the argument, the paper adopts the perspective of network theory to analyse each administration’s strategy toward cyber security and examine the types and characteristics of the US led cyber security cooperation networks in each period. Furthermore, the paper traces the cause of the transformation, using the theory of constitutive institutionalism that focuses on the constitutive interaction of three variablesinterests, institutions and ideas-to explain national security policies.