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A Sciento-text framework to characterize research strength of institutions at fine-grained thematic area level

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Abstract

This paper presents a Sciento-text framework to characterize and assess research performance of leading world institutions in fine-grained thematic areas. While most of the popular university research rankings rank universities either on their overall research performance or on a particular subject, we have tried to devise a system to identify strong research centres at a more fine-grained level of research themes of a subject. Computer science (CS) research output of more than 400 universities in the world is taken as the case in point to demonstrate the working of the framework. The Sciento-text framework comprises of standard scientometric and text analytics components. First of all every research paper in the data is classified into different thematic areas in a systematic manner and then standard scientometric methodology is used to identify and assess research strengths of different institutions in a particular research theme (say Artificial Intelligence for CS domain). The performance of framework components is evaluated and the complete system is deployed on the Web at url: www.universityselectplus.com. The framework is extendable to other subject domains with little modification.

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Notes

  1. http://apps.webofknowledge.com.

  2. http://academic.research.microsoft.com/.

  3. http://www.shanghairanking.com/.

  4. https://www.timeshighereducation.co.uk/.

  5. http://www.topuniversities.com/.

  6. http://www.leidenranking.com/.

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Acknowledgments

This work is supported by research grants from Department of Science and Technology, Government of India (Grant: INT/MEXICO/P-13/2012) and University Grants Commission of India (Grant: F. No. 41-624/2012(SR)). A preliminary version of this work was presented in 20th Science Technology Indicators Conference in Sep. 2015 at Lugano, Switzerland.

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Authors and Affiliations

  1. Department of Computer Science, South Asian University, New Delhi, India

    Ashraf Uddin

  2. Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY, USA

    Jaideep Bhoosreddy

  3. DST-CIMS, Banaras Hindu University, Varanasi, India

    Marisha Tiwari

  4. Department of Computer Science, Banaras Hindu University, Varanasi, 221005, India

    Vivek Kumar Singh

Authors
  1. Ashraf Uddin
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  2. Jaideep Bhoosreddy
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  3. Marisha Tiwari
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  4. Vivek Kumar Singh
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Correspondence to Vivek Kumar Singh.

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Uddin, A., Bhoosreddy, J., Marisha Tiwari et al. A Sciento-text framework to characterize research strength of institutions at fine-grained thematic area level. Scientometrics 106, 1135–1150 (2016). https://doi.org/10.1007/s11192-016-1836-2

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