purpletag 0.1.0

Python Boilerplate contains all the boilerplate you need to create a Python package.

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.
See 'purpletag help <command>' for more information on a specific command.

``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: 1,30,365]

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 365`` will collect all
tweets
| posted in the past 365 days and compute output like the example above.
The
| file name itself will indicate this. For example,
``2014-05-02.365.tags`` is a
| tags file created when running this command on May 2, 2014, collecting
| statistics for the past 365 days.

``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





History
-------

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

* First release on PyPI.