Signed Backbone Extraction

This Python package provides tools to extract the signed backbones of intrinsically dense weighted networks.

Its counterpart in R can be found at https://github.com/furkangursoy/signed.backbones.

Dependecies

1. numpy
2. pandas

Tested for numpy==1.20.1 and pandas==1.2.2 but should work with most versions.

Installation

Use the package manager pip to install signed_backbones.

pip install signed_backbones

Example Usage

import signed_backbones as sb
import pandas as pd

karate_net = pd.read_csv('karate.txt', header=None, sep='\t')

karate_sbb = sb.extract(karate_net, directed = False, significance_threshold = 2.576, vigor_threshold = (-0.1, 0.1))

See examples/KarateViz.ipynb for visualizations of the original Karate network and its extracted signed backbone.

Citation

If you find this software useful in your work, please cite:

Furkan Gursoy and Bertan Badur. "Extracting the signed backbone of intrinsically dense weighted networks".

Reproducibility

The folder reproducibility contains Jupyter notebooks and R Markdown files that are used to create the figures and tables in the manuscript.

Contributing

Please feel free to open an issue for bug reports, change requests, or other contributions.

License

MIT

Packaged with: Flit