Statistical Analysis of Network Data with R

  • Eric D. Kolaczyk
  • Gábor Csárdi

Part of the Use R! book series (USE R, volume 65)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Eric D. Kolaczyk, Gábor Csárdi
    Pages 1-11
  3. Eric D. Kolaczyk, Gábor Csárdi
    Pages 13-28
  4. Eric D. Kolaczyk, Gábor Csárdi
    Pages 29-41
  5. Eric D. Kolaczyk, Gábor Csárdi
    Pages 43-67
  6. Eric D. Kolaczyk, Gábor Csárdi
    Pages 69-83
  7. Eric D. Kolaczyk, Gábor Csárdi
    Pages 85-109
  8. Eric D. Kolaczyk, Gábor Csárdi
    Pages 111-134
  9. Eric D. Kolaczyk, Gábor Csárdi
    Pages 135-159
  10. Eric D. Kolaczyk, Gábor Csárdi
    Pages 161-178
  11. Eric D. Kolaczyk, Gábor Csárdi
    Pages 179-195
  12. Back Matter
    Pages 197-207

About this book

Introduction

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).

Keywords

Network Analysis Network Topology R Random Graph Models

Authors and affiliations

  • Eric D. Kolaczyk
    • 1
  • Gábor Csárdi
    • 2
  1. 1.Boston University ProfessorBostonUSA
  2. 2.Department of StatisticsHarvard University Research AssociateCambridgeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-0983-4
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4939-0982-7
  • Online ISBN 978-1-4939-0983-4
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • About this book