Mixing properties of growing networks and the Simpson's paradox
arXiv:cond-mat/0506509 · doi:10.1103/PhysRevE.74.026122
Abstract
We analyze the mixing properties of growing networks and find that, in some cases, the assortativity patterns are reversed once links' direction is considered: the disassortative behavior observed in such networks is a spurious effect, and a careful analysis reveals genuine positive correlations. We prove our claim by analytical calculations and numerical simulations for two classes of models based on preferential attachment and fitness. Such counterintuitive phenomenon is a manifestation of the well known Simpson's paradox. Results concerning mixing patterns may have important consequences, since they reflect on structural properties as resilience, epidemic spreading and synchronization. Our findings suggest that a more detailed analysis of real directed networks, such as the World Wide Web, is needed.
arXiv comment4 pages, 4 figures, revtex. Minor corrections in the references
References in corpus (15)
- Emergence of scaling in random networks
- Statistical mechanics of complex networks
- The structure and function of complex networks
- Uncovering the overlapping community structure of complex networks in nature and society
- Assortative mixing in networks
- Mixing patterns in networks
- Dynamical and correlation properties of the Internet
- Why social networks are different from other types of networks
- Structure of Growing Networks: Exact Solution of the Barabasi--Albert's Model
- Software systems as complex networks: structure, function, and evolvability of software collaboration graphs
- Class of correlated random networks with hidden variables
- Resilience to damage of graphs with degree correlations
- Rate equation approach for correlations in growing network models
- Loops structure of the Internet at the Autonomous System Level
- Quantitative description and modeling of real networks