2006 CiteSpaceIIDetectVisualEmergTrendsTransientPatternsInScieLite

• (Chen, 2006) ⇒ Chaomei Chen. (2006). “CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature.” In: Journal of the American Society for Information Science and Technology, 57(3). doi:10.1002/asi.20317

Subject Headings:

Quotes

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 expert s, 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.

References

---

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2006 CiteSpaceIIDetectVisualEmergTrendsTransientPatternsInScieLite	Chaomei Chen			CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature		Journal of the American Society for Information Science and Technology	http://cluster.cis.drexel.edu/~cchen/citespace/doc/jasist2006.pdf	10.1002/asi.20317		2006