Generates biased stop word lists for various genres
Project description
Overview
Bias are bugs
Stop words are words which are filtered out before processing of natural language data. Often in text analysis there are non-casual correlations, consider the following documents:
He is an astronaut, he is on Venus
He is an accountant, he is on Earth
She is an astronaut, she is on Mars
Processing these documents into two topics will result in gendered clustering. If we remove the gendered terms:
is an astronaut, is on Venus
is an accountant, is on Earth
is an astronaut, is on Mars
Processing will result in job clustering. Both clusterings are valid, however if you are interested in employing an astronaut, you don’t want male accountants showing up. There are many other examples of non casual relationships occurring in natural language; religion, ethnicity, and age to name a few.
Available genres
English Gendered Terms
US names
More will be available soon. Contribute at https://github.com/gregology/biased-stop-words
Installation
biased-stop-words is available on PyPI
http://pypi.python.org/pypi/biased-stop-words
Install via pip
$ pip install biased-stop-words
Or via easy_install
$ easy_install biased-stop-words
Or directly from biased-stop-words’s git repo <https://github.com/gregology/biased-stop-words>
$ git clone --recursive git://github.com/gregology/biased-stop-words.git $ cd biased-stop-words $ python setup.py install
Basic usage
from biased_stop_words import get_stop_words stop_words = get_stop_words('gendered', 'common-us-names')
Running Test
$ python biased_stop_words/tests.py
Python compatibility
Developed for Python 2 & 3.
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