The article provides an overview of types and characteristics of networks, as well as models for analyzing how complex networks function.
Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Source: Newman, M. E. J. (2003). The structure and function of complex networks (pp. 58): University of Michigan and Santa Fe Institute. http://www-personal.umich.edu/~mejn/courses/2004/cscs535/review.pdf
The article contains several chapters providing an overview of different types of networks and their characteristics, as well as models for analysing them.
A sample of chapters is listed below:
- Types of networks
- Social networks
- Information networks
- Technological networks
- Biological networks
- Properties of networks
- Scale-free networks
- Network resilience
- Community structure
- Random graphs
- The configuration model
- Models of network growth
- Processes taking place on networks
- Search on networks
- Phase transitions on networks
- Other processes on networks