A First Course in Network Science

A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.

Filippo Menczer (Author), Santo Fortunato (Author), Clayton A. Davis (Author)

9781108471138, Cambridge University Press

Hardback, published 30 January 2020

300 pages, 131 b/w illus. 131 colour illus.
25.2 x 19.5 x 1.8 cm, 0.8 kg

'Should be titled the 'Joy of Networks', clearly conveys the fun and power of the science of networks, while providing extensive hands-on exercises with network data.' David Lazer, University Distinguished Professor of Political Science and Computer and Information Science, Northeastern University

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

Preface
Introduction
1. Network elements
2. Small worlds
3. Hubs
4. Directions and weights
5. Network models
6. Communities
7. Dynamics
Appendix A. Python tutorial
Appendix B. NetLogo models
Bibliography
Index.

Subject Areas: Databases & the Web [UNN], Biology, life sciences [PS], Statistical physics [PHS], Combinatorics & graph theory [PBV], Organizational theory & behaviour [KJU], Sociology [JHB], Data analysis: general [GPH], Information theory [GPF]