Python for Graph and Network Analysis
Kurzinformation
inkl. MwSt. Versandinformationen
Artikel zZt. nicht lieferbar
Artikel zZt. nicht lieferbar

Beschreibung
This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications. von Al-Taie, Mohammed Zuhair
Produktdetails
So garantieren wir Dir zu jeder Zeit Premiumqualität.
Über den Autor
- hardcover
- 296 Seiten
- Erschienen 2016
- Wiley-VCH
- paperback
- 420 Seiten
- Erschienen 2013
- Springer
- hardcover
- 320 Seiten
- Erschienen 2013
- Wiley
- Gebunden
- 456 Seiten
- Erschienen 2016
- Cambridge University Press
- Kartoniert
- 232 Seiten
- Erschienen 2017
- O'Reilly
- paperback
- 296 Seiten
- Erschienen 2008
- Springer
- hardcover
- 461 Seiten
- Erschienen 2020
- Cambridge University Press
- Klappenbroschur
- 479 Seiten
- Erschienen 2020
- Rheinwerk Computing
- Kartoniert
- 310 Seiten
- Erschienen 2018
- O'Reilly Media
- Kartoniert
- 418 Seiten
- Erschienen 2008
- Wiley-Blackwell
- paperback
- 570 Seiten
- Erschienen 2005
- World Scientific



