English Letter Frequency Counts: Mayzner Revisited
I did something similar with a 10m Tweet dataset couple of years ago:<p>* <a href="http://ktype.net/wiki/research:articles:progress_20110209#twitter_n-gram_results" rel="nofollow">http://ktype.net/wiki/research:articles:progress_20110209#tw...</a><p>* <a href="http://ktype.net/wiki/research:articles:progress_20110228?s#letter-pair_frequency_table" rel="nofollow">http://ktype.net/wiki/research:articles:progress_20110228?s#...</a><p>I would love to redo this analysis with newer Tweets but alas, don't know where to get a usable corpus. Any suggestions? My goal was to explore many of the concepts from norvig's <a href="http://norvig.com/spell-correct.html" rel="nofollow">http://norvig.com/spell-correct.html</a> using the Tweet dataset to build a better one-finger-keyboard and word-prediction engine for iOS.