Metadata-Version: 2.4
Name: netseg
Version: 0.1.5
Summary: netseg is a python package for measuring segregation and structural polarization in social networks.
Author-email: Onur Tuncay Bal <onurtuncaybal@gmail.com>
Project-URL: Homepage, https://codeberg.org/onurB/netseg
Project-URL: Bug Tracker, https://codeberg.org/OnurB/netseg/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: igraph
Requires-Dist: numpy
Requires-Dist: scipy
Dynamic: license-file


# netseg

```netseg``` is a python and R package for measuring segregation and structural polarization in social networks. It was developed to address several key gaps in the current ecosystem:
<img src="assets/netseg-logo.png" align="right" width="150" alt="netseg logo">
* **A Unified Framework:** While analyzing network segregation and polarization is common, the myriad of existing measures makes cross-network comparisons exceedingly difficult. ```netseg``` provides a centralized toolkit for standardizing these measurements.

* **Extensively Documented:** ```netseg``` is extensively documented. From various case by case usage examples to the advanced null-model selection, it offers a clear guide for your research.

* **Advanced Null-Model Comparison:** Many existing approaches rely on purely random graphs to quantify excess polarization or segregation, a notoriously low baseline. ```netseg``` allows you to use customized network ensembles as null models, enabling robust, comparative segregation analysis.

* **Extensions and Improved Optimization** `netseg` offers extensions for already existing measures, calculating the structural polarization and segregation in directed and undirected networks with multiple groups. ```netseg``` is build on [igraph](https://igraph.org/) and [NumPy](https://numpy.org/) , it offers near bare-metal speed with NumPy's vectorization and igraph's C backend.
## Support and Contact

If you come across any issues, please visit the repository pages.

* [Python Issues](https://codeberg.org/OnurB/netseg)
* [R Issues](https://mbojan.github.io/netseg/)

* Suggestions & Discussions: bal_onur@phd.ceu.edu

## Installation
You can install `netseg` through PyPI with 

```{bash}
pip install netseg
```

Or you can install directly from the source without the blobs with

```{bash}
git clone --filter=blob:none --sparse https://codeberg.org/OnurB/netseg.git
cd netseg
git sparse-checkout set src
pip install .
```
## Documentation
You can reach to the documentation [here.](https://onurb.codeberg.page/netseg/)
