Python for Graph and Network Analysis

✍ Scribed by Mohammed Zuhair Al-Taie and Seifedine Kadry

• Publisher: Springer
• Year: 2017
• Tongue: English
• Leaves: 214
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiii
Theoretical Concepts of Network Analysis....Pages 1-32
Network Basics....Pages 33-47
Graph Theory....Pages 49-64
Social Networks....Pages 65-78
Node-Level Analysis....Pages 79-111
Group-Level Analysis....Pages 113-146
Network-Level Analysis....Pages 147-164
Information Diffusion in Social Networks....Pages 165-184
Back Matter....Pages 185-203