Skip to content

Estimating the relative importance of individuals within a social network using Spark MLlib

License

Notifications You must be signed in to change notification settings

IBMPredictiveAnalytics/MLlib_Pagerank

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MLlib_PageRank

The scenario here is to perform analysis on the social graph using data on email exchanges. We use a small extract from the enron corpus (see enron.csv) listing the source and destination of e-mails. We use the pagerank algorithm to rank enron employees where an email from person A to person B is seen as A in some way endorsing B. Estimating the relative importance of individuals within a social network is a key step for a number of applications including fraud investigation and marketing.

PageRank measure the importance of each vertex in a graph, assuming an edge from u to v represents an endorsement of v's importance by u.

Map


Requirements

  • IBM SPSS Modeler v17.1
  • IBM SPSS Analytic Server 2.1

More information here: IBM Predictive Extensions


Installation instructions

  1. Download the extension: Download
  2. Close IBM SPSS Modeler. Save the .cfe file in the CDB directory, located by default on Windows in "C:\ProgramData\IBM\SPSS\Modeler\17.1\CDB" or under your IBM SPSS Modeler installation directory.
  3. Restart IBM SPSS Modeler, the node will now appear in the Model palette.

License

Apache 2.0

Contributors

About

Estimating the relative importance of individuals within a social network using Spark MLlib

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages