Skip to main content

Node-Level Analysis

  • Chapter
  • First Online:
Python for Graph and Network Analysis

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

  • 7997 Accesses

Abstract

This chapter is concerned with building an understanding of how to do network analysis at the node (ego) level. It shows how to create social networks from scratch, how to import networks, how to find key players in social networks using centrality measures, and how to visualize networks. We will also introduce the important algorithms that are used to gain insights from graphs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Al-Taie, M.Z., Kadry, S. (2017). Node-Level Analysis. In: Python for Graph and Network Analysis. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-53004-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-53004-8_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53003-1

  • Online ISBN: 978-3-319-53004-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics