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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

PREORDER - Expected ship date February 4, 2026

ISBN10: 3032091705
ISBN13: 9783032091703
Publisher: Springer
Published: Feb 4 2026
Pages: 222
Language: English
This book describes a new holistic methodology for analyzing a field of scientific literature using a combination of network and semantic analysis of bibliometric data, in order to identify the main citation patterns and most impactful research in a scientific field. It introduces new centrality indices that take into account more complex parameters of nodes than classical indices, such as group influence and the influence of pivotal vertices on other vertices. Other topics covered by the book include pattern analysis and stability metrics; centrality analysis of article citation networks; journal citation networks; and methods of semantic analysis to analyze trends. The book also shows how to analyze the co-occurrence of terms and to learn more about research trends by dividing articles into topical groups. While the scientific literature of Parkinson's disease (PD) forms the basis of this book, its contents will be useful to researchers in any scientific domain, as well as journal editorial teams, scientific organizations, and investors.

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