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Collects all tweets from the sample Public stream using Twitter's streaming API, and saves them to a file for later use as a corpus.

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General Info

Collects all tweets from the sample Public stream using Twitter's streaming API, and writes them to stdout, which you can redirect to a file for later use as a corpus.

The sample Public stream "Returns a small random sample of all public statuses. The Tweets returned by the default access level are the same, so if two different clients connect to this endpoint, they will see the same Tweets."

This module consumes tweets from the sample Public stream and putes them on a queue. The tweets are then consumed from the queue by writing them to a file in JSON format as sent by twitter, with one tweet per line. This file can then be processed and filtered as necessary to create a corpus of tweets for use with Machine Learning, Natural Language Processing, and other Human-Centered Computing applications.

Usage

First, you will need to configure the script by supplying tokens that are generated by Twitter for your application.

  • Copy the config-sample.yaml file to config.yaml.

  • Follow the instructions in the config file to generate the necessary keys and tokens for your Twitter app, and add them to the config file.

  • Edit the script as needed. Use the following examples as a guide so that you may connect to the appropriate stream in the main() function.

  • Create a virtualenv and install the dependencies from the requirements file.

  • Run the script, redirecting stdout as needed e.g.:

    python twitter_corpus.py > tweet-stream.json
    

Status and error information will be written to stderr.

Statuses/Sample

By default, the script is configured to connect to the sample stream, which "returns a small random sample of all public statuses".

stream.sample()

Statuses/Filter

If you would like to filter tweets by location boxes then be sure to read the location parameter information from the Twitter API. Below is an example to filter tweets for the continental United States.

LOCATIONS = [-124.85, 24.39, -66.88, 49.38,]
stream.filter(locations=LOCATIONS)

If you would like to filter by keywords instead, use the track parameter. Below is an example to filter for some example emoticons.

EMOTICONS = ">:] :-) :) :o) :] :3 :c) :> =] 8) =) :} :^) "
EMOTICONS = EMOTICONS.strip().split(' ')
stream.filter(track=EMOTICONS)

More Information

Please refer to the streaming.py module from the Tweepy library.

Process vs. stdout

If you would like to modify the application to process tweets as they are received instead of writing them to stdout, edit the worker() function as needed.

Relevant Twitter API Documentation

  • Public streams, which describe the types of streams available.
  • Statuses/filter, which describes the limits for the number of keywords, users, and location boxes that you are allowed to use with the filter. Pay special note to the fact that all filters are combined through the OR operator and not the AND operator. For example, specifying both location and track parameters will return a Tweet object that matches either criteria, and not necessarily both.
  • Tweet objects, which are returned by the streams. Describes all the fields present.
  • User objects, which are also embedded into each Tweet object. Describes all the fields present.
  • Location parameter information.
  • Track (keyword) parameter information.

Required Libraries

Tweepy

  • A Python library for accessing the Twitter API.
  • Does all the heavy lifting of connecting to the sample Public stream.
  • Available at: https://github.com/tweepy/tweepy

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Collects all tweets from the sample Public stream using Twitter's streaming API, and saves them to a file for later use as a corpus.

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