diff --git a/ngrams/term_frequencies.py b/ngrams/term_frequencies.py
index 9d43493..2723b1f 100755
--- a/ngrams/term_frequencies.py
+++ b/ngrams/term_frequencies.py
@@ -30,7 +30,7 @@ def remove_punct(sentence):
             new_sentence.append(new_token)
     return new_sentence
 
-def my_tokenizer(text):
+def my_tokenizer(text, mwe_pass):
     # remove stopwords, punctuation, urls, lower case
     # lowercase        
     text = text.lower()
@@ -75,13 +75,13 @@ def my_tokenizer(text):
                 yield token
 
 
-def tf_comments(subreddit_weeks):
+def tf_comments(subreddit_weeks, mwe_pass):
     for key, posts in subreddit_weeks:
         subreddit, week = key
         tfs = Counter([])
         authors = Counter([])
         for post in posts:
-            tokens = my_tokenizer(post.body)
+            tokens = my_tokenizer(post.body, mwe_pass)
             tfs.update(tokens)
             authors.update([post.author])
 
@@ -91,13 +91,13 @@ def tf_comments(subreddit_weeks):
         for author, tf in authors.items():
             yield [False, subreddit, author, week, tf]
 
-def tf_posts(subreddit_weeks):
+def tf_posts(subreddit_weeks, mwe_pass):
     for key, posts in subreddit_weeks:
         subreddit, week = key
         tfs = Counter([])
         authors = Counter([])
         for post in posts:
-            tokens = my_tokenizer(post.title)
+            tokens = my_tokenizer(post.title, mwe_pass)
             tfs.update(tokens)
             authors.update([post.author])
 
@@ -184,7 +184,7 @@ def weekly_tf(partition,
 
     # we follow the approach described in datta, phelan, adar 2017
 
-    outrows = tf_func(subreddit_weeks)
+    outrows = tf_func(subreddit_weeks, mwe_pass)
 
     outchunksize = 10000