Citation Analysis And Dynamics Of Citation Networks

This book deals with the science of science by applying network science methods to citation networks and uniquely presents a physics-inspired model of citation dynamics. This stochastic model of citation dynamics is based on a well-known copying or recursive search mechanism. The measurements covered in this text yield parameters of the model and reveal that citation dynamics of scientific papers is not linear, as was previously assumed. This nonlinearity has far-reaching consequences including non-stationary citation distributions, diverging citation trajectories of similar papers, and runaways or "immortal papers" with an infinite citation lifespan. The author shows us that nonlinear stochastic models of citation dynamics can be the basis for a quantitative probabilistic prediction of citation dynamics of individual papers and of the overall journal impact factor. This book appeals to students and researchers from differing subject areas working in network science and bibliometrics.

Citation analysis—the exploration of reference patterns in the scholarly and scientific literature—has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval. Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest stems from significant improvements in the availability and accessibility of digital bibliographic data (both citation and full text) and of relevant computer technologies. The former provides large amounts of data and the latter the necessary tools for researchers to conduct new types of large-scale citation analysis, even without special access to special data collections. Exciting new developments are emerging this way in many aspects of citation analysis. This book critically examines both theory and practical techniques of citation network analysis and visualization, one of the two main types of citation analysis (the other being evaluative citation analysis). To set the context for its main theme, the book begins with a discussion of the foundations of citation analysis in general, including an overview of what can and what cannot be done with citation analysis (Chapter 1). An in-depth examination of the generally accepted steps and procedures for citation network analysis follows, including the concepts and techniques that are associated with each step (Chapter 2). Individual issues that are particularly important in citation network analysis are then scrutinized, namely: field delineation and data sources for citation analysis (Chapter 3); disambiguation of names and references (Chapter 4); and visualization of citation networks (Chapter 5). Sufficient technical detail is provided in each chapter so the book can serve as a practical how-to guide to conducting citation network analysis and visualization studies. While the discussion of most of the topics in this book applies to all types of citation analysis, the structure of the text and the details of procedures, examples, and tools covered here are geared to citation network analysis rather than evaluative citation analysis. This conscious choice was based on the authors’ observation that, compared to evaluative citation analysis, citation network analysis has not been covered nearly as well by dedicated books, despite the fact that it has not been subject to nearly as much severe criticism and has been substantially enriched in recent years with new theory and techniques from research areas such as network science, social network analysis, or information visualization.

Can the methods of science be directed toward science itself? How did it happen that scientists, scientific documents, and their bibliographic links came to be regarded as mathematical variables in abstract models of scientific communication? What is the role of quantitative analyses of scientific and technical documentation in current science policy and management? Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics answers these questions through a comprehensive overview of theories, techniques, concepts, and applications in the interdisciplinary and steadily growing field of bibliometrics. Since citation indexes came into the limelight during the mid-1960s, citation networks have become increasingly important for many different research fields. The book begins by investigating the empirical, philosophical, and mathematical foundations of bibliometrics, including its beginnings with the Science Citation Index, the theoretical framework behind it, and its mathematical underpinnings. It then examines the application of bibliometrics and citation analysis in the sciences and science studies, especially the sociology of science and science policy. Finally it provides a view of the future of bibliometrics, exploring in detail the ongoing extension of bibliometric methods to the structure and dynamics of the World Wide Web. This book gives newcomers to the field of bibliometrics an accessible entry point to an entire research tradition otherwise scattered through a vast amount of journal literature. At the same time, it brings to the forefront the cross-disciplinary linkages between the various fields (sociology, philosophy, mathematics, politics) that intersect at the crossroads of citation analysis. Because of its discursive and interdisciplinary approach, the book is useful to those in every area of scholarship involved in the quantitative analysis of information exchanges, but also to science historians and general readers who simply wish to familiarize them

The book addresses the issue of interdisciplinary understanding of collaboration on the topic of social network studies. Researchers and practitioners from various disciplines including sociology, computer science, socio-psychology, public health, complex systems, and management science have worked largely independently, each with quite different principles, terminologies, theories. and methodologies. The book aims to fill the gap among these disciplines with a number of the latest interdisciplinary collaboration studies.

This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communities of nations). Part three contains discussions of non-Gaussian laws connected to scientific productivity and presents various deterministic and stochastic models of science dynamics and research productivity. The book shows that many famous fat tail distributions as well as many deterministic and stochastic models and processes, which are well known from physics, theory of extreme events or population dynamics, occur also in the description of dynamics of scientific systems and in the description of the characteristics of research productivity. This is not a surprise as scientific systems are nonlinear, open and dissipative.

Since 2007, the biennial International Conferences on Dynamics in Logistics (LDIC) offers researchersand practitioners from logistics, operations research, production, industrial and electrical engineering aswell as from computer science an opportunity to meet and to discuss the latest developments in thisparticular research domain. From February 23th to 25th 2022 for the eighth time, LDIC 2022 was held inBremen, Germany. Similar to its seven predecessors, the Bremen Research Cluster for Dynamics inLogistics (LogDynamics) organized this conference. The spectrum of topics reaches from the dynamicmodeling, planning and control of processes over supply chain management and maritime logistics toinnovative technologies and robotic applications for cyber-physical production and logistics systems.LDIC 2022 provided a forum for the discussion of advances in that matter. The conference programconsisted of keynote speeches and research papers selected by a severe double-blind reviewing process.Within these proceedings all the papers are published. By this, the proceedings give an interdisciplinaryoutline on the state of the art of dynamics in logistics as well as identify challenges and solutions forlogistics today and tomorrow.

This contributed volume explores the renaissance of general relativity after World War II, when it transformed from a marginal theory into a cornerstone of modern physics. Chapters explore key historical processes related to the theory of general relativity, in addition to presenting a thorough treatment of the relevant science behind these episodes. A broad historiographical framework is introduced first, thus providing the broad context in which the given computational approaches and case studies occurred. Written by an international and interdisciplinary group of expert authors, these chapters will bring readers to a more complete understanding of Einstein’s theory. Specific topics include: Social and citation networks The Fock-Infeld dispute Wheeler’s turn to gravitation theory The position of general relativity in theories of fundamental interactions The pursuit of a quantum theory of gravity The emergence of dark matter in relation to cosmological models Institutional frameworks for gravitational wave search in Europe The Renaissance of General Relativity in Context is ideal for historians, philosophers, and sociologists of science. Students and researchers in physics will also be interested in the topics explored.

The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume.