I shot a quick post over at the Data Driven Security blog explaining how to separate Twitter data gathering from R code via the Ruby
t (github repo) command. Using
t frees R code from having to be a Twitter processor and lets the analyst focus on analysis and visualization, plus you can use
t as a substitute for Twitter GUIs if you’d rather play at the command-line:
$ t timeline ddsecblog @DDSecBlog Monitoring Credential Dumps Plus Using Twitter As a Data Source http://t.co/ThYbjRI9Za @DDSecBlog Nice intro to R + stats // Data Analysis and Statistical Inference free @datacamp_com course http://t.co/FC44FF9DSp @DDSecBlog Very accessible paper & cool approach to detection // Nazca: Detecting Malware Distribution in Large-Scale Networks http://t.co/fqrSaFvUK2 @DDSecBlog Start of a new series by new contributing blogger @spttnnh! // @AlienVault rep db Longitudinal Study Part 1 : http://t.co/XM7m4zP0tr ...
The DDSec post shows how to mine the well-formatted output from the @dumpmon Twitter bot to visualize dump trends over time:
and has the code in-line and over at the DDSec github repo [R].