I have written a few hacks allowing me to do rudimentary text mining against the logs. [1] From readme.txt: This directory contains a number of files and scripts allowing one to do a bit of text mining against the Code4Lib conference IRC log files for 2011. This is just a beginning, and the directory includes: * irclog.txt - the raw log file downloaded from http://irc.code4lib.org/c4l11/static/logs/irclog * log2db.pl - reads the raw log and outputs a tab-delimited file with three columns (date, name, text) * irclog.db - the output of log2db.pl * count.pl - outputs the number of names (n), increases (i), decreases (d), URLs (u), and commands (c) found in the log; useful for seeing what is hot and what is not. * ngrams.pl - given an integer (n), outputs the most frequent n-length phrases; useful to see what words and phrases are used most frequently * concordance.pl - a KWIK index; the simplest of search engines * readme.txt - this file Using these tools one can see that: * Zoia had the most to say * mbklein's karma was increased the most * Zoia's karma was decreased the most * the most popular URL passed around regarded social activities * we tried to sing as many as 196 songs closely followed by anagrams * 28 of the songs weren't found * live streams were mentioned frequently I have to go shovel snow now... [1] initial hacks - http://bit.ly/gMO4op -- Eric Lease Morgan