Fundamentals of Big Data Network Analysis for Research and Industry

Table of contents

1. Cover
2. Title Page
3. Preface
4. About the Authors
5. List of Figures
6. List of Tables
7. 1 Why Big Data?
   1. 1.1 Big Data
   2. 1.2 What Creates Big Data?
   3. 1.3 How Do We Use Big Data?
   4. 1.4 Essential Issues Related to Big Data
   5. References
8. 2 Basic Programs for Analyzing Networks
   1. 2.1 UCINET
   2. 2.2 NetMiner
   3. 2.3 R
   4. 2.4 Gephi
   5. 2.5 NodeXL
   6. References
9. 3 Understanding Network Analysis
   1. 3.1 Defining Social Network Analysis
   2. 3.2 Basic SNA Concepts
   3. 3.3 Social Network Data
   4. References
10. 4 Research Methods Using SNA
    1. 4.1 SNA Research Procedures
    2. 4.2 Identifying the Research Problem and Developing Hypotheses
    3. 4.3 Research Design
    4. 4.4 Acquisition of Network Data
    5. 4.5 Data Cleansing
    6. References
11. 5 Position and Structure
    1. 5.1 Position
    2. 5.2 Cohesive Subgroup
    3. References
12. 6 Connectivity and Role
    1. 6.1 Connection Analysis
    2. 6.2 Role
    3. References
13. 7 Data Structure in NetMiner
    1. 7.1 Sample Data
    2. 7.2 Main Concept
    3. 7.3 Data Preprocessing
    4. Reference
14. 8 Network Analysis Using NetMiner
    1. 8.1 Centrality and Cohesive Subgroup
    2. 8.2 Connectivity and Equivalence
    3. 8.3 Visualization and Exploratory Analysis
15. Appendix A: Visualization
    1. A.1 Spring Algorithm
    2. A.2 Multidimensional Scaling Algorithm
    3. A.3 Cluster Algorithm
    4. A.4 Layered Algorithm
    5. A.5 Circular Algorithm
    6. A.6 Simple Algorithm
    7. References
16. Appendix B: Case Study
    1. Reference
17. Index
18. End User License Agreement