Benchmarking research performance at the university level with information theoretic measures
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This paper presents a new method for comparing universities based on information theoretic measures. The research output of each academic institution is represented statistically by an impact-factor histogram. To this aim, for each academic institution we compute the probability of occurrence of a publication with impact factor in different intervals. Assuming the probabilities associated with a pair of academic institutions our objective is to measure the Information Gain between them. To do so, we develop an axiomatic characterization of relative information for predicting institution-institution dissimilarity. We use the Spanish university system as our scenario to test the proposed methodology for benchmarking three universities with the rest as a case study. For each case we use different scientific fields such as Information and Communication Technologies, Medicine and Pharmacy, and Economics and Business as we believe comparisons must take into account their disciplinary context. Finally we validate the Information Gain values obtained for each case with previous studies.
KeywordsInformation gain Institution-institution similarity Impact-factor histogram Information theoretic measure Information conservation constraint Benchmarking research output
This research was sponsored by the Spanish Board for Science and Technology (MICINN) under grant TIN2010-15157 cofinanced with European FEDER funds. Nicolás Robinson-García is currently supported by a FPU grant from the Spanish Ministerio de Educación y Ciencia. Thanks are due to the reviewers for their constructive suggestions.
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