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Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006)
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- Abstract
- 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.
- Date
- 22. 7.2006 16:11:05
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Samoylenko, I.; Chao, T.-C.; Liu, W.-C.; Chen, C.-M.: Visualizing the scientific world and its evolution (2006)
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Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009)
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Lamb, I.; Larson, C.: Shining a light on scientific data : building a data catalog to foster data sharing and reuse (2016)
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Chen, R.H.-G.; Chen, C.-M.: Visualizing the world's scientific publications (2016)
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Petersen, A.; Münch, V.: STN® AnaVist(TM) holt verborgenes Wissen aus Recherche-Ergebnissen : Neue Software analysiert und visualisiert Marktaufteilung, Forschung und Patentaktivitäten (2005)
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- Source
- Information - Wissenschaft und Praxis. 56(2005) H.5/6, S.319-322
