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Practical Social Network Analysis with Python

  • Krishna Raj P.M.
  • Ankith Mohan
  • K.G. Srinivasa

Part of the Computer Communications and Networks book series (CCN)

Table of contents

  1. Front Matter
    Pages i-xxxi
  2. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 1-23
  3. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 25-44
  4. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 45-56
  5. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 57-85
  6. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 87-100
  7. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 101-108
  8. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 109-144
  9. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 145-172
  10. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 173-188
  11. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 189-202
  12. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 203-232
  13. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 233-243
  14. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 245-278
  15. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 279-299
  16. Krishna Raj P. M., Ankith Mohan, K. G. Srinivasa
    Pages 301-317
  17. Back Matter
    Pages 319-329

About this book

Introduction

This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis.

With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks.

This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.


Keywords

Social Network Analysis Graph Analysis Igraph Stanford Network Analysis Platform (SNAP) Large Scale Networks

Authors and affiliations

  • Krishna Raj P.M.
    • 1
  • Ankith Mohan
    • 2
  • K.G. Srinivasa
    • 3
  1. 1.Department of ISERamaiah Institute of TechnologyBangaloreIndia
  2. 2.Department of ISERamaiah Institute of TechnologyBangaloreIndia
  3. 3.Department of Information TechnologyC.B.P. Government Engineering CollegeJaffarpurIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-96746-2
  • Copyright Information Springer Nature Switzerland AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-96745-5
  • Online ISBN 978-3-319-96746-2
  • Series Print ISSN 1617-7975
  • Series Online ISSN 2197-8433
  • Buy this book on publisher's site