[Sigmetrics] Structural Variation Analysis (SVA)
cc345 at drexel.edu
Fri Sep 18 00:20:51 EDT 2015
The Structural Variation Analysis (SVA) is a computational analytic procedure that aims to identify the novelty of a scientific publication based on how much it differs from its peers' citation patterns.
The underlying theory and a few concept-proving case studies appeared in a 2012 paper in JASIST. The function is now available in the latest release of CiteSpace (4.0 Release 1).
CiteSpace is a freely available Java application for visualizing trends and patterns in scientific literature.
Feedback, comments, and suggestions are welcome.
* Chen, C. (2012) Predictive effects of structural variation on citation counts<http://dx.doi.org/10.1002/asi.21694>. Journal of the American Society for Information Science and Technology, 63(3), 431-449.
* Chen, C. (2014) The Fitness of Information: Quantitative Assessments of Critical Evidence<http://www.amazon.com/gp/product/1118128338/ref=as_li_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1118128338&linkCode=as2&tag=chaomeichensh-20&linkId=6HTSBJWVXIDL43E3>. Wiley.
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