A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools.

Preface; Introduction; 1. Graphs and graph theory; 2. Centrality measures; 3. Random graphs; 4. Small-world networks; 5. Generalised random graphs; 6. Models of growing graphs; 7. Degree correlations; 8. Cycles and motifs; 9. Community structure; 10. Weighted networks; Appendix; References; Author index; Index.

Vito Latora is Professor of Applied Mathematics and Chair of Complex Systems at Queen Mary University of London. Noted for his research in statistical physics and in complex networks, his current interests include time-varying and multiplex networks, and their applications to socio-economic systems and to the human brain.