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How to Use CiteSpace

Chaomei Chen

This book shows you various practical step-by-step instructions as well as the design principles behind them so that readers will be able to create high-quality visualizations and, more importantly, to make sense of various patterns and what we can do with them.

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About

About

About the Book

What are the landmarks and critical paths in a field of research? What can we learn from published scholarly works? CiteSpace is designed to find answers to these questions through interactive visual explorations of actionable patterns and trends. This book explains the underlying principles and analytic processes of learning the state of the art of a field of research. This edition is based on the CiteSpace Advanced version of 6.1.R2. Currently, it contains chapters on download and installation of the software, collecting bibliographic data from the Web of Science, CSSCI, CNKI, and PubMed, and step-by-step demonstrations of creating and interacting with visualizations of a variety of topics. Chapters on other data sources will be updated, including Scopus and Dimensions, and they will be incrementally incorporated in subsequent versions of the e-books.

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Author

About the Author

Chaomei Chen

I am a Professor of Informatics in the College of Computing and Informatics at Drexel University, Philadelphia, USA. I am the founding editor and the Editor in Chief of Information Visualization, published quarterly by SAGE. I am also the founding editor and the Chief Field Editor of Frontiers in Scholarly Metrics and Analytics, an open-access journal. I am the author of several books, including Representing Scientific Knowledge: The Role of Uncertainty (Springer, 2017), The Fitness of Information: Quantitative Assessments of Critical Evidence (Wiley, 2014), Mapping Scientific Frontiers: The Quest for Knowledge Visualization (2nd Ed.) (Springer, 2013), and Information Visualization: Beyond the Horizon (Springer, 2004, 2006). I have been developing and maintaining CiteSpace - a computational tool for visualizing patterns and trends in scientific literature.

Contents

Table of Contents

1 What is CiteSpace for?

  1. 1.1 A Quick Overview
  2. 1.2 Typical Questions to Answer
  3. 1.3 How should I cite CiteSpace?
  4. 1.4 How Can I Learn More about CiteSpace
  5. 1.5 Problems, Bug Reports, or Feature Requests
  6. 1.7 Topics Covered in This Book

2 How to Download and Install CiteSpace

  1. 2.0 Different Versions of CiteSpace
  2. 2.1 Download CiteSpace
  3. 2.2 Java Virtual Machine
  4. 2.3 Install CiteSpace
  5. 2.4 How Many Records Can CiteSpace Handle?
  6. 2.5 Configure the Memory Allocation for CiteSpace
  7. 2.6 Change the Locale
  8. 2.7 Uninstall or Refresh CiteSpace
  9. 2.9 On Mac or Unix-based Systems

3 Get Started with CiteSpace

  1. 3.1 Launch CiteSpace
  2. 3.2 The Demo Project: Demo 1: Terrorism Research (1996-2003)
  3. 3.3 Interact with CiteSpace
  4. 3.4 Control Panel
  5. 3.5 Burst Detection
  6. 3.6 Cluster Explorer
  7. 3.7 Visual Encoding and Metrics
  8. 3.8 Automatically Generated Cluster Labels
  9. 3.9 Save and Open Visualizations

4 Work with Data from the Web of Science

  1. 4.1 Data Collection and My Philosophy
  2. 4.2 Extract Data from the Web of Science
  3. 4.3 Duplicate Removal
  4. 4.3 Visual Exploration
  5. 4.3 Summary

10 Scopus

  1. 10.1 Search on Scopus
  2. 10.2 Export Results in RIS
  3. 10.3 Organizing the files
  4. 10.4 Set project properties with converted Scopus data
  5. 10.5 Execute the project
  6. 10.6 Export Cited References to RIS or EndNote
  7. 10.7 Merge bibliographic records from Scopus and the Web of Science
  8. 10.7 Summary

11 CSSCI

  1. 11.1 Data Format
  2. 11.2 Format Conversion
  3. 11.3 Configuring a Project with CSSCI Data
  4. 11.4 Document Co-Citation Analysis
  5. 11.5 Hybrid Networks
  6. 11.6 Summary

12 CNKI

  1. 12.1 Data Format
  2. 12.2 Data Collection from CNKI
  3. 12.3 Converting the Data Format
  4. 12.4 Configuring a Project with CNKI Data
  5. 12.5 Creating a Network of Co-occuring Keywords
  6. 12.5 Examples of Visualizations Created with CNKI Data
  7. 12.6 Summary

16 PubMed

  1. 16.1 Search on PubMed
  2. 16.2 Data Format
  3. 16.3 Converting PubMed Records from the NBIB Format
  4. 16.4 Configuring a Project with PubMed Data
  5. 16.5 Constructing Networks from PubMed Data
  6. 16.6 Creating Concept Trees with PubMed Data
  7. 16.7 Burst Detection with Extracted Terms
  8. 16.8 Summary

Examples of Visualizations

  1. Cascading Citation Expansion
  2. Cluster Views of a Network
  3. Points of Interest
  4. Dual-May Overlays
  5. Link Walkthrough
  6. Structural Variation Analysis
  7. CSSCI
  8. CNKI
  9. Timeline Views
  10. SVG
  11. Uncertainties
  12. Examplar Cases

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