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CiteSpace is a freely available Java application for visualizing and analyzing trends and patterns in scientific literature. It is designed as a tool for progressive knowledge domain visualization (Chen, 2004). It focuses on finding critical points in the development of a field or a domain, especially intellectual turning points and pivotal points. Detailed case studies are given in (Chen, 2006) and other publications. CiteSpace provides various functions to facilitate the understanding and interpretation of network patterns and historical patterns, including identifying the fast-growth topical areas, finding citation hotspots in the land of publications, decomposing a network into clusters, automatic labeling clusters with terms from citing articles, geospatial patterns of collaboration, and unique areas of international collaboration.
CiteSpace supports structural and temporal analyses of a variety of networks derived from scientific publications, including collaboration networks, author co-citation networks, and document co-citation networks. It also supports networks of hybrid node types such as terms, institutions, and countries, and hybrid link types such as co-citation, co-occurrence, and directed citing links.
The primary source of input data for CiteSpace is the Web of Science. Search for a topic of interest and download the search results (including full records and references). CiteSpace will handle the data from there. CiteSpace also provides some simple interfaces for obtaining data from PubMed, arXiv, ADS, and NSF Award Abstracts. CiteSpace can be used to generate geographic map overlays viewable in Google Earth based on the locations of authors.