Metadata-Version: 2.4
Name: apunim
Version: 1.0.2
Summary: Polarization attribution in annotation tasks
Project-URL: Homepage, https://github.com/dimits-ts/apunim
Project-URL: Issues, https://github.com/dimits-ts/apunim/issues
Author-email: Dimitris Tsirmpas <dim.tsirmpas@aueb.gr>
License-Expression: GPL-3.0
License-File: LICENSE
Keywords: annotation,annotators,background,disagreemnt,polarization,socio-demographic
Classifier: Development Status :: 3 - Alpha
Classifier: Framework :: Sphinx
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Version Control :: Git
Classifier: Typing :: Typed
Requires-Python: >=3.12
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: statsmodels
Provides-Extra: dev
Requires-Dist: build; extra == 'dev'
Requires-Dist: furo; extra == 'dev'
Requires-Dist: sphinx; extra == 'dev'
Requires-Dist: twine; extra == 'dev'
Description-Content-Type: text/markdown

# Apunim: Attributing polarization to sociodemographic groups

Repository housing the implementation of the Aposteriori Unimodality ("Apunim") metric, which attributes polarization in annotation to specific annotator groups. See the accompanying paper for details:  [Quantifying and Attributing Polarization to Annotator Groups]([link pending](https://arxiv.org/abs/2602.06055)).

Includes two functions: `dfu`, which calculates the Distance From Unimodality (and also implements the normalized variant - nDFU), and `aposteriori-unimodality`, which calculates the apunim metric and associated pvalue.

See the [online documentation](https://dimits-ts.github.io/apunim/) for high-level notes, usage examples, and module documentation.

Installation is possible through PyPi: `pip install apunim`.