robustrao: An Extended Rao-Stirling Diversity Index to Handle Missing Data

A collection of functions to compute the Rao-Stirling diversity index (Porter and Rafols, 2009) <doi:10.1007/s11192-008-2197-2> and its extension to acknowledge missing data (i.e., uncategorized references) by calculating its interval of uncertainty using mathematical optimization as proposed in Calatrava et al. (2016) <doi:10.1007/s11192-016-1842-4>. The Rao-Stirling diversity index is a well-established bibliometric indicator to measure the interdisciplinarity of scientific publications. Apart from the obligatory dataset of publications with their respective references and a taxonomy of disciplines that categorizes references as well as a measure of similarity between the disciplines, the Rao-Stirling diversity index requires a complete categorization of all references of a publication into disciplines. Thus, it fails for a incomplete categorization; in this case, the robust extension has to be used, which encodes the uncertainty caused by missing bibliographic data as an uncertainty interval. Classification / ACM - 2012: Information systems ~ Similarity measures, Theory of computation ~ Quadratic programming, Applied computing ~ Digital libraries and archives.

Downloads:

Linking:

Please use the canonical form https://CRAN.R-project.org/package=robustrao to link to this page.