• Title/Summary/Keyword: co-citation

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Exploratory Analysis of Platform Government Research (플랫폼 정부 연구의 탐색적 분석)

  • Shin, Sun-Young;Suh, Chang-Kyo
    • The Journal of Information Systems
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    • v.29 no.1
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    • pp.159-179
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    • 2020
  • Purpose: We present a scientometric review of the literature on platform government to serve three primary purposes: First, to cluster researches on platform government based on the research issues; second, to identify the major papers, authors, and keywords in the domain; and third, to explore the promising research areas of platform government. Design/methodology/approach: We collected the platform government research from Web of Science, and analyzed 1,536 articles that was published during time span of 1998-2019. Next, co-citation networks are constructed and analyzed by using CiteSpace to visualize the domain clusters and dynamic research trends in the platform government domain. Findings: We identified 13 sub areas of the platform government research: global investigation, consumer product quality, digital agora, civic crowd funding, and open data use etc. We also visualize the top 20 references with the strongest citation bursts, co-authors network, co-occurring keyword network, and timeline of co-citation clusters.

Centrality Measures for Bibliometric Network Analysis (계량서지적 네트워크 분석을 위한 중심성 척도에 관한 연구)

  • Lee Jae-Yun
    • Journal of the Korean Society for Library and Information Science
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    • v.40 no.3
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    • pp.191-214
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    • 2006
  • Recently, some bibliometric researchers tried to use the centrality analysis methods and the centrality measures which are standard tools in social network analysis. However the traditional centrality measures originated from social network analysis could not deal with weighted networks such as co-citation networks. In this study. new centrality measures for analyzing bibliometric networks with link weights are suggested and applied to three real network data, including an author co-citation network, a co-word network, and a website co-link network. The results of centrality analyses in these three cases can be regarded as Promising the usefulness of suggested centrality measures, especially in analyzing the Position and influence of each node in a bibliometric network.

Author co-citation mapping and changes of intellectual structure in a subject area : with reference to Korean history (저자용인용 메핑과 학문의 지적구조변화)

  • 조명희
    • Journal of the Korean Society for information Management
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    • v.10 no.1
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    • pp.65-96
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    • 1993
  • This research fulfills two objectives of the study relating to the analysis of changing intellectual structure and its development of Korean history during 1980s: 1) investigation of intellectural structures of two successive time periods using author co-citation study analysis: 2) validation of the results of author co-citation analysis using assessments of experts collected from scholarly reviews and direct data drawn from the researchers in the area of Korean history. Three approaches to multivariate analysis as multi-dimensional scaling, cluster analysis, and factor analysis are used to display the inter-author relationships in the author similarity matrix.

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Author Co-citation Analysis for Digital Twin Studies (디지털 트윈 연구의 저자 동시인용 분석)

  • Kim, Sumin;Suh, Chang-Kyo
    • The Journal of Information Systems
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    • v.28 no.3
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    • pp.39-58
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    • 2019
  • Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.

The Intellectual Structure of Business Analytics by Author Co-citation Analysis : 2002 ~ 2020 (저자동시인용분석에 의한 Business Analytics 분야의 지적 구조 분석: 2002 ~ 2020)

  • Lim, Hyae Jung;Suh, Chang Kyo
    • The Journal of Information Systems
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    • v.30 no.1
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    • pp.21-44
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    • 2021
  • Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

A Visualization Based Analysis on Dynamic Bandwidth Allocation Algorithms for Optical Networks

  • Kamran Ali Memon;Khalid Husain Mohmadani ;Saleemullah Memon;Muhammad Abbas;Noor ul Ain
    • International Journal of Computer Science & Network Security
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    • v.23 no.8
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    • pp.204-209
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    • 2023
  • Dynamic Bandwidth Allocation (DBA) methods in telecommunication network & systems have emerged with mechanisms for sharing limited resources in a rapidly growing number of users in today's access networks. Since the DBA research trends are incredibly fast-changing literature where almost every day new areas and terms continue to emerge. Co - citation analysis offers a significant support to researchers to distinguish intellectual bases and potentially leading edges of a specific field. We present the visualization based analysis for DBA algorithms in telecommunication field using mainstream co-citation analysis tool-CiteSpace and web of science (WoS) analysis. Research records for the period of decade (2009-2018) for this analysis are sought from WoS. The visualization results identify the most influential DBA algorithms research studies, journals, major countries, institutions, and researchers, and indicate the intellectual bases and focus entirely on DBA algorithms in the literature, offering guidance to interested researchers on more study of DBA algorithms.

An Identification of the Image Retrieval Domain from the Perspective of Library and Information Science with Author Co-citation and Author Bibliographic Coupling Analyses

  • Yoon, JungWon;Chung, EunKyung;Byun, Jihye
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.4
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    • pp.99-124
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    • 2015
  • As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

Analyzing and Visualizing the Intellectual Structure of Data Science (데이터사이언스 연구의 지적 구조 분석 및 시각화)

  • Park, Hyoungjoo
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.18-29
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    • 2022
  • The purpose of this exploratory study is to examine the intellectual structure of data science. For this purpose, this research examined a total of 17,997 bibliographies on data science indexed in Web of Science(WoS) of Clarivate Analytics from 2012 to 2021. This research applied methods such as descriptive analysis, citation analysis, co-author network analysis, co-occurrence network analysis, bibliographic coupling analysis, and co-citation analysis. This research contributes to finding the research directions of future data science topics.

Analysis of Factors Influencing Patent Citations (특허 인용에 영향을 미치는 요인 분석)

  • Yoo, Jae-Bok;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.1
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    • pp.103-118
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    • 2010
  • Recently, the valuation of patented technology has been greatly emphasized, and patent citation has been accepted as a very useful index of this technology. In this study, we performed correlation analyses between the patent citation counts and 17 explanatory variables of morphological, technological, and conceptual factors with a test dataset of U.S. patents in five subject fields. Seven variables having 5% or more standardized variances($r^2$) with patent citation counts were identified; number of pages, number of claims, reference-average-citation rate, patent increase/decrease rate, strength of bibliographic coupling, co-citation counts and document similarity. The result of the ANOVA test shows that the mean values of these variables vary among most subject fields.

Journal Citation Analysis for Library Services on Interdisciplinary Domains: A Case Study of Department of Biotechnology, Y University (학제적 분야의 정보서비스를 위한 학술지 인용 분석에 관한 연구: Y대학교 생명공학과를 중심으로)

  • Yu, So-Young;Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.25 no.4
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    • pp.283-308
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    • 2008
  • In this study, we testify that network structural attributes of a citation network can explain other aspects of journal citation behaviors and the importances of journals. And we also testify various citation impact indicators of journals including JIF and h-index to verify the difference among them especially focused on their ability to explain an institution's local features of citation behaviors. An institutional citation network is derived using the articles published in 2006-2007 by biotechnology faculties of Y University. And various journal citation impact indicators including JIF, SJR, h-index, EigenFactor, JII are gathered from different service sites such as Web of Science, SCImago, EigenFactor.com, Journal-Ranking.com. As a results, we can explain the institution's 5 research domains with inter-citation network. And we find that the co-citation network structural features can show explanations on the patterns of institutional journal citation behavior different from the simple cited frequency of the institution or patterns based on general citation indicators. Also We find that journal ranks with various citation indicators have differences and it implies that total-based indices, average-based indices, and hybrid index(h-index) explain different aspects of journal citation pattern. We also reveal that the coverage of citation DB doesn't be a matter in the journal ranking. Analyzing the citation networks derived from an institution's research outputs can be a useful and effective method in developing several library services.