Why social networks are different from other types of networks
Santa Fe Institute · University of Michigan–Ann Arbor
Abstract
We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or network transitivity and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups…
Citation impact
- FWCI
- 24.30
- Percentile
- 100%
- References
- 43
Authors
2Topics & keywords
- Transitive relation
- Cluster analysis
- Mixing (physics)
- Variation (astronomy)
- Mixing patterns
- Computer science
- Social network (sociolinguistics)
- Complex network
- Reduced inequalities