Network Metrics and Density Analysis

 
Social Network Metrics
 
 
Types of network metrics
 
Group level
Density
Components
Isolates
Cliques
Centralization
Degree
Closeness
Betweenness
Factions
Core-periphery
 
Node level
Centrality
Degree
Indegree
Outdegree
Closeness
Betweenness
Visualization
Netdraw
Mage
QAP
Statistical metrics
MDS
Cluster analysis
 
Preparing the data
 
Most graph-based metrics require symmetric,
dichotomous (binary) data
Symmetrization
Minimum (captures reciprocal ties)
Maximum (most inclusive)
Dichotomize
Valued data are typically ordinal
Mean, median or modal values
 
Network Density
 
The proportion of ties that exist out of all
possible ties
 
For valued data the sum of all tie strengths
divided by all possible ties
 
Density is a course measure
 
Density = .33
Degree centralization = 10%
 
Density = .33
Degree centralization = 60%
 
Centrality versus centralization
 
Centrality is a node level metric; each node
has a centrality score representing it’s position
within the network
 
Centralization is a group level metric
indicating the extent to which the network is
dominated by one or a few nodes
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Explore different types of network metrics such as density, centrality, and visualization techniques. Learn how to prepare data for graph-based analysis and understand the concept of network density. Gain insights into measuring network density and centralization in social networks.

  • Network Metrics
  • Density Analysis
  • Centrality
  • Data Preparation
  • Visualization

Uploaded on Sep 24, 2024 | 0 Views


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  1. Social Network Metrics

  2. Types of network metrics Group level Density Components Isolates Cliques Centralization Degree Closeness Betweenness Factions Core-periphery Node level Centrality Degree Indegree Outdegree Closeness Betweenness Visualization Netdraw Mage QAP Statistical metrics MDS Cluster analysis

  3. Preparing the data Most graph-based metrics require symmetric, dichotomous (binary) data Symmetrization Minimum (captures reciprocal ties) Maximum (most inclusive) Dichotomize Valued data are typically ordinal Mean, median or modal values

  4. Network Density The proportion of ties that exist out of all possible ties For valued data the sum of all tie strengths divided by all possible ties

  5. Density is a course measure Density = .33 Degree centralization = 10% Density = .33 Degree centralization = 60%

  6. Centrality versus centralization Centrality is a node level metric; each node has a centrality score representing it s position within the network Centralization is a group level metric indicating the extent to which the network is dominated by one or a few nodes

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