Skip to content

Instantly share code, notes, and snippets.

Created Oct 24, 2013
What would you like to do?
from pig_util import outputSchema
import nltk
def top_5_bigrams(tweets):
tokenized_tweets = [ nltk.tokenize.WhitespaceTokenizer().tokenize(t[0]) for t in tweets ]
bgm = nltk.collocations.BigramAssocMeasures()
finder = nltk.collocations.BigramCollocationFinder.from_documents(tokenized_tweets)
top_5 = finder.nbest(bgm.likelihood_ratio, 5)
return [ ("%s %s" % (s[0], s[1]),) for s in top_5 ]
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment