nltk.corpus.reader.TwitterCorpusReader

class documentation

class TwitterCorpusReader(CorpusReader): (source)

Constructor: TwitterCorpusReader(root, fileids, word_tokenizer, encoding)

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))

Method	`__init__`	smaller units, including but not limited to words.
Method	`docs`	Returns the full Tweet objects, as specified by Twitter documentation on Tweets
Method	`raw`	Return the corpora in their raw form.
Method	`strings`	Returns only the text content of Tweets in the file(s)
Method	`tokenized`	as a list of words, screenanames, hashtags, URLs and punctuation symbols.
Method	`_read_tweets`	Assumes that each line in `stream` is a JSON-serialised object.
Instance Variable	`_word_tokenizer`	Undocumented

Inherited from CorpusReader:

Method	`__repr__`	Undocumented
Method	`abspath`	Return the absolute path for the given file.
Method	`abspaths`	Return a list of the absolute paths for all fileids in this corpus; or for the given list of fileids, if specified.
Method	`citation`	Return the contents of the corpus citation.bib file, if it exists.
Method	`encoding`	Return the unicode encoding for the given corpus file, if known. If the encoding is unknown, or if the given file should be processed using byte strings (str), then return None.
Method	`ensure_loaded`	Load this corpus (if it has not already been loaded). This is used by LazyCorpusLoader as a simple method that can be used to make sure a corpus is loaded -- e.g., in case a user wants to do help(some_corpus).
Method	`fileids`	Return a list of file identifiers for the fileids that make up this corpus.
Method	`license`	Return the contents of the corpus LICENSE file, if it exists.
Method	`open`	Return an open stream that can be used to read the given file. If the file's encoding is not None, then the stream will automatically decode the file's contents into unicode.
Method	`readme`	Return the contents of the corpus README file, if it exists.
Class Variable	`root`	Undocumented
Method	`_get_root`	Undocumented
Instance Variable	`_encoding`	The default unicode encoding for the fileids that make up this corpus. If `encoding` is None, then the file contents are processed using byte strings.
Instance Variable	`_fileids`	A list of the relative paths for the fileids that make up this corpus.
Instance Variable	`_root`	The root directory for this corpus.
Instance Variable	`_tagset`	Undocumented

def __init__(self, root, fileids=None, word_tokenizer=TweetTokenizer(), encoding='utf8'): (source) ¶

overrides nltk.corpus.reader.CorpusReader.__init__

smaller units, including but not limited to words.

Parameters
root	The root directory for this corpus.
fileids	A list or regexp specifying the fileids in this corpus.
word_tokenizer	Tokenizer for breaking the text of Tweets into
encoding	Undocumented

def docs(self, fileids=None): (source) ¶

Returns the full Tweet objects, as specified by Twitter documentation on Tweets

from JSON. :rtype: list(dict)

Returns
the given file(s) as a list of dictionaries deserialised

def raw(self, fileids=None): (source) ¶

Return the corpora in their raw form.

def strings(self, fileids=None): (source) ¶

Returns only the text content of Tweets in the file(s)

Returns
list(str)	the given file(s) as a list of Tweets.

def tokenized(self, fileids=None): (source) ¶

as a list of words, screenanames, hashtags, URLs and punctuation symbols.

Returns
list(list(str))	the given file(s) as a list of the text content of Tweets as

def _read_tweets(self, stream): (source) ¶

Assumes that each line in stream is a JSON-serialised object.

_word_tokenizer = (source) ¶

Undocumented