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Neighborhood link-based features

Sometimes, the feature values of neighboring nodes have an effect on behavior. In this exercise, you will look at the attribute value of neighboring nodes and compute their average. You will do this for degree, triangles, transitivity, and betweenness.

You need to:

  • Multiply the adjacency matrix with the network attribute you want to find the average of, to obtain the overall value in the neighborhood.
  • To get the average, divide by the node's degree, given by the vector degree which has been pre-loaded.
  • Finally, convert the result to a vector and assign to network as a node attribute.

Cet exercice fait partie du cours

Predictive Analytics using Networked Data in R

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Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Extract the average degree of neighboring nodes
V(network)$averageDegree <- 
    as.vector(AdjacencyMatrix %*% V(network)$___) / degree
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