Cluster your Facebook friends

January 22, 2012

(This article was first published on, and kindly contributed to R-bloggers)

Last week, I came across two interesting posts by Romain François and Petr Simecek:

As coincidence would have it, I also came across an older introductory post about social network analysis (Grey’s Anatomy Network of Sexual Relations) which could actually complement quite well the two posts above.

Using the igraph package, it is very easy to use the Girvan-Newman algorithm to automatically detect your groups/clusters of friends. The code below show how to display the names of your friends on the plot.


Here is the full code to create the chart above:

To leave a comment for the author, please follow the link and comment on their blog: offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Recent popular posts

Most visited articles of the week

  1. R Passes SAS in Scholarly Use (finally)
  2. How to write the first for loop in R
  3. Installing R packages
  4. R tutorials
  5. Using apply, sapply, lapply in R
  6. In-depth introduction to machine learning in 15 hours of expert videos
  7. Free e-book: Exploring Data Science
  8. How to perform a Logistic Regression in R
  9. What are the Best Machine Learning Packages in R?


Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training


CRC R books series

Contact us if you wish to help support R-bloggers, and place your banner here.

RSS Jobs for R users

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)