diff --git a/newspaper/text.py b/newspaper/text.py
index 6ceb763f..8c4d88ad 100644
--- a/newspaper/text.py
+++ b/newspaper/text.py
@@ -75,7 +75,7 @@ def remove_punctuation(self, content):
             content = content.encode('utf-8')
         return content.translate(self.TRANS_TABLE, string.punctuation)
 
-    def candiate_words(self, stripped_input):
+    def candidate_words(self, stripped_input):
         return stripped_input.split(' ')
 
     def get_stopword_count(self, content):
@@ -83,10 +83,10 @@ def get_stopword_count(self, content):
             return WordStats()
         ws = WordStats()
         stripped_input = self.remove_punctuation(content)
-        candiate_words = self.candiate_words(stripped_input)
+        candidate_words = self.candidate_words(stripped_input)
         overlapping_stopwords = []
         c = 0
-        for w in candiate_words:
+        for w in candidate_words:
             c += 1
             if w.lower() in self.STOP_WORDS:
                 overlapping_stopwords.append(w.lower())
@@ -104,7 +104,7 @@ class StopWordsChinese(StopWords):
     def __init__(self, language='zh'):
         super(StopWordsChinese, self).__init__(language='zh')
 
-    def candiate_words(self, stripped_input):
+    def candidate_words(self, stripped_input):
         # jieba builds a tree that takes a while. avoid building
         # this tree if we don't use the chinese language
         from .packages import jieba
@@ -122,7 +122,7 @@ def __init__(self, language='ar'):
     def remove_punctuation(self, content):
         return content
 
-    def candiate_words(self, stripped_input):
+    def candidate_words(self, stripped_input):
         import nltk
         s = nltk.stem.isri.ISRIStemmer()
         words = []
@@ -143,10 +143,10 @@ def get_stopword_count(self, content):
             return WordStats()
         ws = WordStats()
         stripped_input = self.remove_punctuation(content)
-        candiate_words = self.candiate_words(stripped_input)
+        candidate_words = self.candidate_words(stripped_input)
         overlapping_stopwords = []
         c = 0
-        for w in candiate_words:
+        for w in candidate_words:
             c += 1
             for stop_word in self.STOP_WORDS:
                 overlapping_stopwords.append(stop_word)