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) 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) .
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.