purpletag 0.1.3

A tool to track hashtags used by members of the U.S. congress.

purpletag
=========

A tool to track polarized hashtags used by members of the U.S. congress.

Install
-------

``pip install purpletag``

or, from source:

::

git clone https://github.com/casmlab/purpletag.git
cd purpletag
python setup.py install

Configuration
-------------

purpletag depends on `twutil <https://github.com/tapilab/twutil>`__ for
collecting data from Twitter. You'll need to put your credentials in the
following environmental variables:

- ``TW_CONSUMER_KEY``
- ``TW_CONSUMER_SECRET``
- ``TW_ACCESS_TOKEN``
- ``TW_ACCESS_TOKEN_SECRET``

purpletag also depends on a configuration file (see
```sample.cfg`` <sample.cfg>`__ for an example). By default, it is
assumed to be in ``~/.purpletag``, but you can specify a custom location
by setting the ``PURPLE_CFG`` environmental variable.

By default, all data will be written to ``/data/purpletag``, but you can
change this in the config file.

purpletag fetches the list of legislators and their Twitter handles from
http://www.govtrack.us/; these URLs are also specified in the config.

Getting started
---------------

purpletag consists of a number of command-line tools to collect, parse,
and analyze tweets sent by members of Congress.

To see the list of commands:

::

$ purpletag -h
usage: purpletag [--help] <command> [<args>...]

The most commonly used purpletag commands are:
collect Collect tweets from members of congress, stored in json
parse Parse tweet json
score Create score files containing polarization scores for hashtags and MOCs.
serve Launch a web service to visualize results.
See 'purpletag help <command>' for more information on a specific command.

The expected use case is that ``collect`` is run continuously, then
``parse``, ``score``, ``serve`` are run once daily. There is also
support for using historical data (see the ``-s`` option of ``collect``
and the ``-d`` option of ``parse``).

``collect``
~~~~~~~~~~~

This command will fetch tweets from all members of congress listed in
``twitter.yaml``.

::

purpletag collect -h
usage:
purpletag collect [options]
purpletag collect (-t | --track | -s | --search) [options]

Options
-h, --help
-o, --output <file> output path
-r, --refresh-handles fetch latest twitter handles for politicians
-t, --track collect tweets in real time using streaming API
-s, --search search historical tweets using search API

There are two modes of operation:

- ``track``: Use the Twitter Streaming API to collect tweets in
real-time.
- ``search``: Use the Twitter REST API to collect the most recent 3,200
tweets from each legislator.

Output is stored in ``/data/purpletag/jsons``.

You probably want to use ``search`` to first collect all historical
tweets, then run ``track`` to collect all tweets going forward.
**Note:** ``search`` will take a long time to run (hours), since the
script sleeps to wait out the rate limits imposed by the REST API.

``parse``
~~~~~~~~~

This command will parse all the collected tweets in
``/data/purpletag/jsons`` and extract the hashtags used by each
legislator.

::

purpletag parse -h
usage: purpletag parse [options]

Parse .json files into .tags files.

Options
-h, --help help
-t <timespans> sliding window timespans [default: 1,7,30]
-d <days> number of historical days to simulate [default: 1]

The output looks like this:

::

markwarner whistleblowers:1 studentdebt:1 nova:1 f22:1
repwestmoreland jobs:1 nationaldayofprayer:2 benghazi:3

For example, this indicates that Lynn Westmoreland used the hashtag
#jobs once, #nationaldayofprayer twice, and #benghazi three times.

The ``-t`` parameter indicates a list of timespans to use when
aggregating these statistics. For example ``purpletag parse -t 30`` will
parse all tweets posted in the past 30 days and compute output like the
example above. The file name itself will indicate this. For example,
``2014-05-02.30.tags`` is a tags file created when running this command
on May 2, 2014, collecting statistics for the past 30 days.

The ``-d`` parameter allows you to simulate running this for a number of
days in the past. This is useful after running ``purpletag collect -s``
to collect all historical data (up to 3,200 per legislator), then
generating tags files as if you had been running this daily.

Output is stored in ``/data/purpletag/tags``.

``score``
~~~~~~~~~

This command scores hashtags according to their polarity.

::

purpletag score -h
usage: purpletag score [options]

Compute polarity scores for all .tags files that we haven't yet processed.

Options
-h, --help help
-r, --refresh-mocs fetch latest legislator information from GovTrack
-c, --counts use hashtag count features instead of binary features
-o, --overwrite overwrite existing .scores files

These produce ``.scores`` files, one per ``.tags`` file. E.g.,
``2014-05-02.365.scores`` contains the scores for the hashtags used for
the 365 days prior to May 2, 2014. The scores range from -1 (liberal) to
+1 (conservative).

::

demandavote -0.004258
getcovered -0.003548
raisethewage -0.003548
.
.
.
senatemustact 0.001499
fairnessforall 0.001799
tcot 0.002249

Output is stored in ``/data/purpletag/scores``.

``serve``
~~~~~~~~~

This command will launch a simple web server to visualize tag polarity
over time, using ```dygraphs`` <http://dygraphs.com/>`__

::

purpletag serve -h
usage: purpletag serve [options]

Launch a web service to visualize results.

Options
-h, --help help
-n <tags> number of tags to show from each party [default: 100]

The web data is stored in ``/data/purpletag/web``. The default port is
set by the config file. So http://0.0.0.0:8000/1.html might look
something like this:

.. figure:: https://raw.githubusercontent.com/casmlab/purpletag/master/docs/sample-graph.png
:alt: sample

sample





History
-------

0.1.3 (2014-05-22)
++++++++++++++++++
* Bug fixes in parse
* Install web data
* Enable time series selection
* Graph ranks instead of scores
* UI tweaks

0.1.1 (2014-05-15)
++++++++++++++++++

* Add UI support
* Bug fixes
* standardize Chi-square scores
* support historical parsing


0.1.0 (2014-05-02)
++++++++++++++++++

* First release on PyPI.