Analysis and Visualization of Citation Networks
Analysis and Visualization of Citation Networks

Author: Dangzhi Zhao

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 189

ISBN-13: 3031022912

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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

Graph Drawing Software
Graph Drawing Software

Author: Michael Jünger

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 381

ISBN-13: 3642186386

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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.

Measuring Scholarly Impact
Measuring Scholarly Impact

Author: Ying Ding

Publisher: Springer

Published: 2014-11-06

Total Pages: 351

ISBN-13: 3319103776

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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.

CiteSpace
CiteSpace

Author: Chaomei Chen

Publisher: Nova Science Publishers

Published: 2016

Total Pages: 0

ISBN-13: 9781536102802

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CiteSpace is a freely available computer program written in Java for visualizing and analyzing literature of a scientific domain. A knowledge domain is broadly defined in order to capture the notion of a logically and cohesively organized body of knowledge. It may range from specific topics such as post-traumatic stress disorder to fields of study lacking clear-cut boundaries, such as research on terrorism or regenerative medicine. CiteSpace takes bibliographic information, especially citation information from the Web of Science, and generates interactive visualizations. Users can explore various patterns and trends uncovered from scientific publications, and develop a good understanding of scientific literature much more efficiently than they would from an unguided search through literature. The full text of many scientific publications can be accessed with a single click through the interactive visualization in CiteSpace. At the end of a session, CiteSpace can generate a summary report to summarize key information about the literature analyzed. This book is a practical guide not only on how to operate the tool but also on why the tool is designed and what implications of various patterns that require special attention. This book is written with a minimum amount of jargon. It uses everyday language to explain what people may learn from the writings of scholars of all kinds.

Visualization Analysis and Design
Visualization Analysis and Design

Author: Tamara Munzner

Publisher: CRC Press

Published: 2014-12-01

Total Pages: 422

ISBN-13: 1466508930

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Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques

Analysis of Biological Networks
Analysis of Biological Networks

Author: Björn H. Junker

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 278

ISBN-13: 1118209915

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An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.

Asian Education Miracles
Asian Education Miracles

Author: Gregory Arief D. Liem

Publisher: Routledge

Published: 2018-11-19

Total Pages: 312

ISBN-13: 1351719882

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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.

Atlas of Science
Atlas of Science

Author: Katy Borner

Publisher: MIT Press

Published: 2010-09-17

Total Pages: 267

ISBN-13: 0262014459

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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.

Statistical Analysis of Network Data with R
Statistical Analysis of Network Data with R

Author: Eric D. Kolaczyk

Publisher: Springer

Published: 2014-05-22

Total Pages: 214

ISBN-13: 1493909835

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Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

Graph Analysis and Visualization
Graph Analysis and Visualization

Author: Richard Brath

Publisher: John Wiley & Sons

Published: 2015-01-30

Total Pages: 544

ISBN-13: 1118845870

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Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.