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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Bibliometric Analysis by Network Models: Identifying Trends in Scientific Literature

Bibliometric Analysis by Network Models: Identifying Trends in Scientific Literature

Aleskerov, Fuad
Khutorskaya, Olga
Stepochkina, Anna

Hardcover

Series: Contemporary Systems Thinking

Medical ReferenceCognitionProbability & Statistics

ISBN10: 3032091705
ISBN13: 9783032091703
Publisher: Springer
Published: Jan 3 2026
Pages: 222
Weight: 1.11
Height: 0.76 Width: 6.44 Depth: 9.41
Language: English
The book contains new models of bibliometric analysis based on centrality measures in network analysis, pattern analysis and stability analysis. A distinctive feature of these centrality measures is that they account for the parameters of vertices and group influence of vertices to a vertex. This reveals specific groups of publications, authors, terms, journals and affiliations of the authors depending on different parameters of publications. Pattern analysis and stability analysis allow the tendencies in developing of the field of research over years to be revealed. These new models are illustrated by an analysis of 39,811 articles on various aspects of Parkinson's disease, published between 2015 and 2021. This methodology can be useful for researchers of any scientific domain, because it enables them to identify key and actively developing trends as well as major players in the field. Moreover, this approach allows to determine main tendencies in the entire research community as well as in the specific parts of it that may have gone unnoticed before. The obtained results of the analysis are useful not only for researchers but also for journals, editorial teams, scientific organizations, and investors.

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