Scale-free network

As explained in Graph Algorithms for Data Science

A scale-free network is a network whose highly uneven degree distribution is characterized by a small number of high-degree hubs and many low-degree nodes.

A scale-free network has a highly uneven degree distribution: many nodes have few links, while a small number of hubs have many links. section 5.0

Analyze the pattern by inspecting node degree distributions and comparing them with random-network distributions as part of broader network characterization. section 5.0

Figure 5.2 Scale-free network degree distribution

Use the scale-free degree-distribution figure to recognize the concentration of links around a small number of high-degree nodes. section 5.0

How Graph Algorithms for Data Science covers it

How deep it goes

Presents the hub-dominated degree-distribution pattern and contrasts it with random networks.

Examples

Compares random-network and scale-free-network degree-distribution figures.

What you can do after

Evaluate network structure by inspecting degree distributions and recognizing hub concentration.

How it connects

Connects scale-free networks with degree distribution, random networks, network metrics, and social network analysis.

liveBookmanning.com

Read Graph Algorithms for Data Science on liveBook Get the book at manning.com

Related concepts

• networkkind of · A network is a system of connected entities and links that enables communication or represents relationships among those entities.
• preferential attachment modelproduced by · The preferential attachment model is a network-growth model in which nodes with more existing connections are more likely to receive new connections.

This explainer was generated by Manning's knowledge graph from the text of Graph Algorithms for Data Science. The section links point to the parts of the book it draws on.