Create data structure needed for classifying data: a list of tuples in the form of ([data], label)

Create a list of liberal hashtags
Create a list of conservative hashtags
Label each one separate from the extraction process
Extend an overarching list called HASHTAGS with both conservative and liberal tuples.
HASHTAGS is in the correct data structure.
WIP.
Program can extract features from a new document (ie, list of hashtags) and return a dictionary of hashtags that are present (value = True) and that are not present (value = False).

In main(), extract hashtags from lib tweets to a list of liberal hashtags. Do the same for conservative tweets. A variable called 'classifier' adds a label to the list and creates a tuple. HASHTAGS is a list of these tuples.

By feeding the output of each function into the next function:
get_unique_hashtags -> get_hashtags_as_features -> extract_features returns a dictionary of 'hits' or matches in a given document.