<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def clean_list_of_twitter_list(list_of_twitter_lists, sent_tokenize, _treebank_word_tokenize, tagger, lemmatizer, lemmatize, stopset, first_cap_re, all_cap_re, digits_punctuation_whitespace_re, pos_set):
 """ Extracts the sets of keywords for each Twitter list. Inputs: - list_of_twitter_lists: A python list of Twitter lists in json format. - lemmatizing: A string containing one of the following: "porter", "snowball" or "wordnet". Output: - list_of_keyword_sets: A list of sets of keywords (i.e. not a bag-of-words) in python set format. - list_of_lemma_to_keywordbags: List of python dicts that map stems/lemmas to original topic keywords. """

    list_of_keyword_sets = list()
    append_keyword_set = list_of_keyword_sets.append

    list_of_lemma_to_keywordbags = list()
    append_lemma_to_keywordbag = list_of_lemma_to_keywordbags.append

    if list_of_twitter_lists is not None:
        for twitter_list in list_of_twitter_lists:
            if twitter_list is not None:
                keyword_set, lemma_to_keywordbag = clean_twitter_list(twitter_list,
                                                                      sent_tokenize, _treebank_word_tokenize,
                                                                      tagger, lemmatizer, lemmatize, stopset,
                                                                      first_cap_re, all_cap_re, digits_punctuation_whitespace_re,
                                                                      pos_set)
                append_keyword_set(keyword_set)
                append_lemma_to_keywordbag(lemma_to_keywordbag)

    return list_of_keyword_sets, list_of_lemma_to_keywordbags