x-index: Identifying core competency and thematic research strengths of institutions using an NLP and network based ranking framework

Hiran H. Lathabai, Abhirup Nandy and Vivek Kumar Singh ()
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Hiran H. Lathabai: Banaras Hindu University
Abhirup Nandy: Banaras Hindu University
Vivek Kumar Singh: Banaras Hindu University

Scientometrics, 2021, vol. 126, issue 12, No 11, 9557-9583

Abstract: Abstract The currently prevailing international ranking systems for institutions are limited in their assessment as they only provide assessments either at an overall level or at very broad subject levels such as Science, Engineering, Medicine, etc. While these rankings have their own usage, they cannot be used to identify best institutions in a specific subject (say Computer Science) by taking into account their performance in different thematic areas of research of the given subject (say Artificial Intelligence or Machine Learning or Computer Vision etc. for the subject Computer Science). This paper tries to bridge this gap by proposing a framework that uses the NLP and Network approach for identifying the core competency of institutions and their thematic research strengths. The core competency can be viewed as a measure of breadth of research capability of an institution in a given subject, whereas thematic research strength can be viewed as depth of research of the institution in a specific theme of a subject. The working of the framework is demonstrated in the area of Computer Science for 195 Indian institutions. The framework can be useful for institutions and the scientometrics research community as a system providing a detailed assessment of the core competency and the research strengths of institutions in different thematic areas. The framework and outcomes can also be useful for funding agencies in devising programs for ‘performance-based funding’ in ‘thrust areas’ or ‘national priority areas’.

Keywords: Core competency; Expertise indices; Research strength; Thematic strength; x-index (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11192-021-04188-3

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