Analysis And Visualization Of Citation Networks

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.

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

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.

After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts: they follow a uniform scheme and can be read independently from each other. The text covers many industrial applications.

This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.

Science maps that can help us understand and navigate the immense amount of results generated by today's science and technology. Cartographic maps have guided our explorations for centuries, allowing us to navigate the world. Science maps have the potential to guide our search for knowledge in the same way, allowing us to visualize scientific results. Science maps help us navigate, understand, and communicate the dynamic and changing structure of science and technology—help us make sense of the avalanche of data generated by scientific research today. Atlas of Science, featuring more than thirty full-page science maps, fifty data charts, a timeline of science-mapping milestones, and 500 color images, serves as a sumptuous visual index to the evolution of modern science and as an introduction to “the science of science”—charting the trajectory from scientific concept to published results. Atlas of Science, based on the popular exhibit, “Places & Spaces: Mapping Science”, describes and displays successful mapping techniques. The heart of the book is a visual feast: Claudius Ptolemy's Cosmographia World Map from 1482; a guide to a PhD thesis that resembles a subway map; “the structure of science” as revealed in a map of citation relationships in papers published in 2002; a visual periodic table; a history flow visualization of the Wikipedia article on abortion; a globe showing the worldwide distribution of patents; a forecast of earthquake risk; hands-on science maps for kids; and many more. Each entry includes the story behind the map and biographies of its makers. Not even the most brilliant minds can keep up with today's deluge of scientific results. Science maps show us the landscape of what we know.

This book defines the application of Information Technology’s systematic and automated knowledge mapping methodology to collect, analyze and report nanotechnology research on a global basis. The result of these analyses is be a systematic presentation of the state of the art of nanotechnology, which will include basic analysis, content analysis, and citation network analysis of comprehensive nanotechnology findings across technology domains, inventors, institutions, and countries.