• Title/Summary/Keyword: Journal citation network

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Thematic Trends in the Research on Green Urbanism (그린 어바니즘의 국제 동향과 주요 화제)

  • Jeong, Sang-kyu;Jeon, Sook-ja;Ban, Yong-un;Park, Joon-young
    • Land and Housing Review
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    • v.12 no.2
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    • pp.61-78
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    • 2021
  • This study aims to understand the thematic trends globally developed in the 'Green Urbanism' related research. Research methodology is based on systemic review of international literature published for the past 20 years period between 2000 and 2020. The specific methods applied include not only literature search by citation, co-authorship, and co-occurrence but social network analysis in order to find correlations among the publication. The correlations are visualized and analysed using VOSviewer and Ucinet software. The analysis indicates that total of 51 studies were carried out by 89 authors from 54 institutions across 21 countries during the period. The majority of the research was done by a country-specific study and only a few research were collaborative studies with other countries. The most common theme that occurred in the early years was 'sustainability and the theme evolved toward specific ones such as 'built environment', 'infrastructure', and 'health'. Having considered that climate change has become a global challenge, green urbanism is expected to be a future direction to pursue environmentally sustainable urban spaces. This study also implies that governance, policy support, and intervention are crucial factors in developing sustainable urban spaces.

Keyword Analysis of Research on Consumption of Children and Adolescents Using Text Mining (텍스트마이닝을 활용한 아동, 청소년 대상 소비관련 연구 키워드 분석)

  • Jin, Hyun-Jeong
    • Journal of Korean Home Economics Education Association
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    • v.33 no.4
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    • pp.1-13
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    • 2021
  • The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

Introducing Keyword Bibliographic Coupling Analysis (KBCA) for Identifying the Intellectual Structure (지적구조 규명을 위한 키워드서지결합분석 기법에 관한 연구)

  • Lee, Jae Yun;Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.39 no.1
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    • pp.309-330
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    • 2022
  • Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

Bibliometric Analysis on Health Information-Related Research in Korea (국내 건강정보관련 연구에 대한 계량서지학적 분석)

  • Jin Won Kim;Hanseul Lee
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.411-438
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    • 2024
  • This study aims to identify and comprehensively view health information-related research trends using a bibliometric analysis. To this end, 1,193 papers from 2002 to 2023 related to "health information" were collected through the Korea Citation Index (KCI) database and analyzed in diverse aspects: research trends by period, academic fields, intellectual structure, and keyword changes. Results indicated that the number of papers related to health information continued to increase and has been decreasing since 2021. The main academic fields of health information-related research included "biomedical engineering," "preventive medicine/occupational environmental medicine," "law," "nursing," "library and information science," and "interdisciplinary research." Moreover, a co-word analysis was performed to understand the intellectual structure of research related to health information. As a result of applying the parallel nearest neighbor clustering (PNNC) algorithm to identify the structure and cluster of the derived network, four clusters and 17 subgroups belonging to them could be identified, centering on two conglomerates: "medical engineering perspective on health information" and "social science perspective on health information." An inflection point analysis was attempted to track the timing of change in the academic field and keywords, and common changes were observed between 2010 and 2011. Finally, a strategy diagram was derived through the average publication year and word frequency, and high-frequency keywords were presented by dividing them into "promising," "growth," and "mature." Unlike previous studies that mainly focused on content analysis, this study is meaningful in that it viewed the research area related to health information from an integrated perspective using various bibliometric methods.

Forecasting the Future Korean Society: A Big Data Analysis on 'Future Society'-related Keywords in News Articles and Academic Papers (빅데이터를 통해 본 한국사회의 미래: 언론사 뉴스기사와 사회과학 학술논문의 '미래사회' 관련 키워드 분석)

  • Kim, Mun-Cho;Lee, Wang-Won;Lee, Hye-Soo;Suh, Byung-Jo
    • Informatization Policy
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    • v.25 no.4
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    • pp.37-64
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    • 2018
  • This study aims to forecast the future of the Korean society via a big data analysis. Based upon two sets of database - a collection of 46,000,000 news on 127 media in Naver Portal operated by Naver Corporation and a collection of 70,000 academic papers of social sciences registered in KCI (Korea Citation Index of National Research Foundation) between 2005-2017, 40 most frequently occurring keywords were selected. Next, their temporal variations were traced and compared in terms of number and pattern of frequencies. In addition, core issues of the future were identified through keyword network analysis. In the case of the media news database, such issues as economy, polity or technology turned out to be the top ranked ones. As to the academic paper database, however, top ranking issues are those of feeling, working or living. Referring to the system and life-world conceptual framework suggested by $J{\ddot{u}}rgen$ Habermas, public interest of the future inclines to the matter of 'system' while professional interest of the future leans to that of 'life-world.' Given the disparity of future interest, a 'mismatch paradigm' is proposed as an alternative to social forecasting, which can substitute the existing paradigms based on the ideas of deficiency or deprivation.

Research Trend and Futuristic Guideline of Platform-Based Business in Korea (플랫폼 기반 비즈니스에 대한 국내 연구동향 및 미래를 위한 가이드라인)

  • Namn, Su Hyeon
    • Management & Information Systems Review
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    • v.39 no.1
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    • pp.93-114
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    • 2020
  • Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.