Analysis and Visualization of Citation Networks

Analysis and Visualization of Citation Networks

Dangzhi Zhao, Andreas Strotmann,
ISBN: 9781608459384 | PDF ISBN: 9781608459391
Copyright © 2015 | 207 Pages | Publication Date: 02/01/2015

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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

About the Author(s)

Dangzhi Zhao, School of Library and Information Studies, University of Alberta, Canada
Dangzhi Zhao is Associate Professor in the School of Library and Information Studies at the University of Alberta, Canada. Dangzhi earned her Ph.D. from the School of Library and Information Studies at The Florida State University, U.S., and her M.S. and B.S. from the Department of Library and Information Science at Peking University, China. Her research and teaching interests are in the areas of information systems, bibliometrics, scholarly communication, and knowledge network analysis and visualization as well as their application in information retrieval and digital libraries.

Andreas Strotmann, ScienceXplore, Bad Schandau, Germany
Andreas Strotmann studied Mathematics, Physics, and Linguistics at the University of Cologne, where he also spent many years as a staff scientist supporting computational applications in the sciences and the humanities, including in mathematics, physics, biology, linguistics, education, and publishing. He earned his doctorate in Computer and Information Science from The Florida State University. He has worked as a researcher at the University of Cologne, the University of Alberta, and the GESIS Leibniz Institute for the Social Sciences. For the past decade, he has been working closely with Dangzhi Zhao on improving scientometric methodology.

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