Affiliations based bibliometric analysis of publications on parkinson’s disease

Fuad Aleskerov, Olga Khutorskaya (), Viacheslav Yakuba (), Anna Stepochkina () and Ksenia Zinovyeva ()
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Olga Khutorskaya: Institute of Control Sciences of Russian Academy of Sciences
Viacheslav Yakuba: National Research University Higher School of Economics
Anna Stepochkina: National Research University Higher School of Economics
Ksenia Zinovyeva: National Research University Higher School of Economics

Computational Management Science, 2024, vol. 21, issue 1, No 13, 14 pages

Abstract: Abstract Parkinson’s disease is the second most common neurodegenerative disorder in the world. Thousands of scientific works are published every year. We have analyzed more than 3 thousand organizations, who have published works on various aspects of parkinson’s disease in the period from 2015 to 2021. We have evaluated 4 classical centrality indices (In-degree, Eigenvector, Pagerank and Betweenness) and 2 new centrality indices. The new indices allow to take into account group influence and to identify pivotal nodes. Using the method, we have extracted the most influential organizations in the scientific area of parkinson’s disease. Stability analysis allows us to measure the value of dynamic changes in the network during the period under consideration.

Keywords: Parkinson’s disease; Network analysis; Citations; Centrality (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10287-023-00495-7

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