code: def keywords(text):
      
      text = split_words(text)
      numWords = len(text)  # of words before removing blacklist words
      freq = Counter(x for x in text if x not in stopWords)
  
      minSize = min(10, len(freq))  # get first 10
      keywords = {x: y for x, y in freq.most_common(minSize)}  # recreate a dict
  
      for k in keywords:
          articleScore = keywords[k]*1.0 / numWords
          keywords[k] = articleScore * 1.5 + 1
  
      return keywords
docs: get the top 10 keywords and their frequency scores
      ignores blacklisted words in stopWords,
      counts the number of occurrences of each word