Analysis of Facebook status updates

December 29, 2010

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

The Facebook Data Team has published an analysis of the status updates of Facebook users, by categorizing words according to the 68 categories of the Linguistic Inquiry and Word Count Dictionary, and tabulating the frequencies of their use. It's fairly interesting to see this kind of analysis applied to Facebook, but unfortunately doesn't reveal much in the way of "A-ha!" insights. For example, this chart of the frequency of six categories of words expressed throughout the day shows pretty much what you'd expect:

Facebook words
(I do wonder whether "Hour of Day" is in local time or all mapped to the same timezone, though: I'd expect the variation to be more pronounced if the analysis were based on local time, and if not I'd have to assume this represents US-based Facebook users only.)

Notable for R users is that all of the charts in the Facebook post were clearly created with Hadley Wickham's ggplot2 package. If you haven't tried ggplot2 yet, check out the ggplot2 website for resources for creating beautiful graphics with R. If you're already a ggplot2 user, you might have missed that it was updated just before Christmas with improvements to legends and axes and several bug fixes. Read the update announcement for the full details.

Facebook Data Team: What’s on your mind


To leave a comment for the author, please follow the link and comment on their blog: Revolutions. 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...

Tags: , ,

Comments are closed.


Mango solutions

plotly webpage

dominolab webpage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training




CRC R books series

Six Sigma Online Training

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

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)