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  3. Predictive Analytics using Networked Data in R

Exercise

Extract PageRank features

In this exercise, you will compute a few PageRank scores and add them as features to the network.

When personalizing, use the prior churners in the network as the restart vector. That is, include the argument personalized = V(network)$Churn.

The default damping value is 0.85.

Instructions 1/4

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  • 1

    Compute the default PageRank score, extract the vector and add it as an attribute to network called pr_0.85.

  • 2

    Compute the PageRank score with damping factor 0.2 and add it to network as pr_0.20.

  • 3

    Compute the default personalized PageRank score and call it perspr_0.85. Look at the instructions above to see how.

  • 4

    Compute the personalized PageRank score with damping factor 0.99 and name it perspr_0.99.