Bibliometric Analysis by Network Models

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.

Fuad Aleskerov is the Head of the International Centre of Decision Analysis and Choice, the Head of the Department of Mathematics for Economics at the National Research University Higher School of Economics in Moscow, Russia, the Head of the Laboratory of Choice Theory and Decision Analysis at the Institute of Control Sciences of the Russian Academy of Sciences, and a Member of Academia Europaea among other scientific societies. He is the author of 12 books and more than 200 articles. Olga Khutorskaya is a Senior Researcher at the Institute of Control Sciences of Russian Academy of Sciences. She is a specialist on medical cybernetics, an author of more than 60 articles and 2 patents in the field related to Parkinson's disease and other neurodegenerative diseases. Anna Stepochkina is a Researcher at the International Centre of Decision Choice and Analysis at the Higher School of Economics in Moscow, Russia. She specializes in the analysis of network and bibliometric data, particularly in data preprocessing, centrality and stability analysis. Her publications focus on the network analysis of scientific research on Parkinson's disease. Viacheslav Yakuba is a Senior Researcher at the Institute of Control Sciences of the Russian Academy of Sciences and at the International Centre of Decision Choice and Analysis at the Higher School of Economics in Moscow, Russia. His current research interests focus on centrality analysis of networks as well as software implementation of the algorithms of newly developed centrality and stability indices in the networks. He has over 70 publications. Ksenia Zinovyeva is a Researcher at the International Centre of Decision Choice and Analysis at the Higher School of Economics in Moscow, Russia. Her work primarily focuses on network analysis, with a special emphasis in the field of bibliometric analysis. She has published several articles exploring citation patterns in publications related to Parkinson's disease research.