Analysis Of Citation Networks
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| Author | : Dangzhi Zhao |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 209 |
| Release | : 2015-02-01 |
| Genre | : Computers |
| ISBN | : 160845939X |
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.
| Author | : Michael Golosovsky |
| Publisher | : Springer Nature |
| Total Pages | : 121 |
| Release | : 2019-09-26 |
| Genre | : Science |
| ISBN | : 3030281698 |
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.
| Author | : Mohammad Gouse Galety |
| Publisher | : John Wiley & Sons |
| Total Pages | : 260 |
| Release | : 2022-04-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1119836735 |
SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.
| Author | : Dangzhi Zhao |
| Publisher | : Springer Nature |
| Total Pages | : 189 |
| Release | : 2022-06-01 |
| Genre | : Computers |
| ISBN | : 3031022912 |
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. Table of Contents: Acknowledgment / Dedications /Foundations of Citation Analysis / Conducting Citation Network Analysis: Steps, Concepts, Techniques, and Tools / Field Delineation and Data Sources for Citation Analysis / Disambiguation in Citation Network Analysis / Visualization of Citation Networks / Appendix 3.3 / Appendix 5.4.2 / Bibliography / Author Biographies
| Author | : Eric D. Kolaczyk |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 397 |
| Release | : 2009-04-20 |
| Genre | : Computers |
| ISBN | : 0387881468 |
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
| Author | : Nicola De Bellis |
| Publisher | : Scarecrow Press |
| Total Pages | : 451 |
| Release | : 2009-03-09 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 0810867141 |
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
| Author | : Gregory Arief D. Liem |
| Publisher | : Routledge |
| Total Pages | : 312 |
| Release | : 2018-11-19 |
| Genre | : Education |
| ISBN | : 1351719882 |
With a focus on Asian contexts, this book brings together knowledge on how values and practices, embedded and practised in the classroom, school, family, and the society at large, can influence students’ motivation, engagement and psychological well-being. The book synthesizes research on students and systems from culturally diverse Asian countries and economies, including Cambodia, Hong Kong-China, Indonesia, Japan, Korea, the Philippines, Singapore, Chinese Taipei, Thailand, the United Arab Emirates, and beyond. The book takes special interest in applying the insights gained from understanding students’ motivation, engagement, and well-being within their sociocultural contexts. Importantly, chapters in the book are grounded on thorough theoretical reviews and sound empirical findings, which together inform practical applications to enhance the motivation, engagement, and well-being of students in the Asian region. Taken together, this book will serve as a comprehensive and authoritative source for scholars, researchers, and practitioners (teachers, school policy makers, and educators in general) who are interested in examining and enhancing student motivation, engagement, and well-being from Asian perspectives.
| Author | : Anita Valmarska |
| Publisher | : |
| Total Pages | : 66 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
| Author | : Henk F. Moed |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 334 |
| Release | : 2006-03-30 |
| Genre | : Science |
| ISBN | : 1402037147 |
This book is written for members of the scholarly research community, and for persons involved in research evaluation and research policy. More specifically, it is directed towards the following four main groups of readers: – All scientists and scholars who have been or will be subjected to a quantitative assessment of research performance using citation analysis. – Research policy makers and managers who wish to become conversant with the basic features of citation analysis, and about its potentialities and limitations. – Members of peer review committees and other evaluators, who consider the use of citation analysis as a tool in their assessments. – Practitioners and students in the field of quantitative science and technology studies, informetrics, and library and information science. Citation analysis involves the construction and application of a series of indicators of the ‘impact’, ‘influence’ or ‘quality’ of scholarly work, derived from citation data, i.e. data on references cited in footnotes or bibliographies of scholarly research publications. Such indicators are applied both in the study of scholarly communication and in the assessment of research performance. The term ‘scholarly’ comprises all domains of science and scholarship, including not only those fields that are normally denoted as science – the natural and life sciences, mathematical and technical sciences – but also social sciences and humanities.
| Author | : Ali Sina Önder |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
We investigate divisions within the citation network in economics using citation data between 1990 and 2010. We consider all partitions of top institutions into two equal-sized clusters and pick the one that minimizes cross-cluster citations. The strongest division is much stronger than could be expected to be found under idiosyncratic citation patterns and is consistent with the reputed freshwater/saltwater division in macroeconomics. The division is stable over time but varies across the fields of economics.
