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.
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