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: Assumes that each line in ``stream`` is a JSON-serialised object.
code: def _read_tweets(self, stream):
      """
      Assumes that each line in ``stream`` is a JSON-serialised object.
      """
      tweets = []
      for i in range(10):
          line = stream.readline()
          if not line:
              return tweets
          tweet = json.loads(line)
          tweets.append(tweet)
      return 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 5 for calling the TwitterCorpusReader obj's underlying member method code with example usage: obj._read_tweets(stream) and returns: tweets, tweets