Practical Social Network Analysis with Python

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Raj P.M., Krishna (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Mohan, Ankith (http://id.loc.gov/vocabulary/relators/aut), Srinivasa, K.G (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Σειρά:Computer Communications and Networks,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Chapter 1. Basics of Graph Theory
  • Chapter 2. Graph Structure of the Web
  • Chapter 3. Random Graph Models
  • Chapter 4. Small World Phenomena
  • Chapter 5. Graph Structure of Facebook
  • Chapter 6. Peer-To-Peer Networks
  • Chapter 7. Signed Networks
  • Chapter 8. Cascading in Social Networks
  • Chapter 9. Influence Maximisation
  • Chapter 10. Outbreak Detection
  • Chapter 11. Power Law
  • Chapter 12. Kronecker Graphs
  • Chapter 13. Link Analysis
  • Chapter 14. Community Detection
  • Chapter 15. Representation Learning on Graph.