class_docstr: Reader for corpora that consist of Tweets represented as a list of line-delimited JSON.
  
  Individual Tweets can be tokenized using the default tokenizer, or by a
  custom tokenizer specified as a parameter to the constructor.
  
  Construct a new Tweet corpus reader for a set of documents
  located at the given root directory.
  
  If you made your own tweet collection in a directory called
  `twitter-files`, then you can initialise the reader as::
  
      from nltk.corpus import TwitterCorpusReader
      reader = TwitterCorpusReader(root='/path/to/twitter-files', '.*\.json')
  
  However, the recommended approach is to set the relevant directory as the
  value of the environmental variable `TWITTER`, and then invoke the reader
  as follows::
  
     root = os.environ['TWITTER']
     reader = TwitterCorpusReader(root, '.*\.json')
  
  If you want to work directly with the raw Tweets, the `json` library can
  be used::
  
     import json
     for tweet in reader.docs():
         print(json.dumps(tweet, indent=1, sort_keys=True))
docstr: :return: the given file(s) as a list of the text content of Tweets as
      as a list of words, screenanames, hashtags, URLs and punctuation symbols.
  
  :rtype: list(list(str))
code: def tokenized(self, fileids=None):
      """
      :return: the given file(s) as a list of the text content of Tweets as
          as a list of words, screenanames, hashtags, URLs and punctuation symbols.
  
      :rtype: list(list(str))
      """
      tweets = self.strings(fileids)
      tokenizer = self._word_tokenizer
      return [tokenizer.tokenize(t) for t in tweets]
  
file_path: nltk/nltk/corpus/reader/twitter.py
imports: import json
  import os
  from nltk.corpus.reader.api import CorpusReader
  from nltk.corpus.reader.util import StreamBackedCorpusView, ZipFilePathPointer, concat
  from nltk.tokenize import TweetTokenizer
label_desc: Use image node_id 4 for calling the TwitterCorpusReader obj's underlying member method code with example usage: obj.tokenized(fileids) and returns: unknown