CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature.
This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conc...
| Publicado en: | Journal of the American Society for Information Science & Technology Vol. 57; no. 3; pp. 359 - 378 |
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| Formato: | case study forms questionnaire/scale research tables/charts Journal Article |
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Wiley-Blackwell
Feb2006
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106132946&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106132946 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15322882 IGD jtl: Journal of the American Society for Information Science & Technology issn: 15322882 maglogo: Y pubinfo: dt: Feb2006 vid: 57 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 106132946 2009345231 10.1002/asi.20317 106132946 ppf: 359 ppct: 19 formats: tig: atl: CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. aug: au: Chen C affil: College of Information Science and Technology, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104-2875 sug: subj: Publishing Trends Scholarship Science Algorithms Citation Analysis Computer Graphics Funding Source Questionnaires Human ab: This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature-an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified. pubtype: Academic Journal doctype: case study forms questionnaire/scale research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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