Text analysis using R

Just a brief post to express my excitement at generating some (meaningful) results using R. While many might see it as early days, this is the first tangible list of incidence of key emotions from a Twitter stream relating to Sony mobiles:

> dataSet <- read.csv("SonyUKMentions.csv")
> em <- classify_emotion(dataSet$Summary, algorithm = "bayes")
> print(xtable(table(em[, "BEST_FIT"]), caption = "Tweet emotion"))
% latex table generated in R 2.15.1 by xtable 1.7-0 package
% Fri Oct 05 16:39:53 2012
\begin{table}[ht]
\begin{center}
\begin{tabular}{rr}
  \hline
 & V1 \\
  \hline
anger &  21 \\
  disgust &   7 \\
  fear &  13 \\
  joy & 275 \\
  sadness &  12 \\
  surprise &  12 \\

All that effort for the last 6 lines! I am going to carry on experimenting with the sentiment package, apply it to other feeds and try some other packages, possibly involving graphs...