Analyzing a FriendFeed group with Ruby and R

January 5, 2010

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

FriendFeed is a social media service, where groups of people can post interesting information from the Web, and "like" or comment posts from others. Statistical Bioinformatician Neil Saunders is a member of the "Life Scientists" group, and has posted an analysis of the group’s activity in 2009 to his blog. He used Ruby and the FriendFeed API to extract the data (group members, posts, comments, and "like"s), and then used R to analyze and visualize the data. For example, here’s a look at the daily traffic in posts, comments, and likes represented as a calendar heat map.


You can see all of the Ruby and R code used to implement this and other analyses (What makes a popular post? Is there a relationship between "like" and comment activity?) at the link below.

What You’re Doing Is Rather Desperate: The Life Scientists at FriendFeed: 2009 summary

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