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.
Tested for numpy==1.20.1 and pandas==1.2.2 but should work with most versions.
Use the package manager pip to install signed_backbones.
pip install signed_backbones
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.
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".
The folder reproducibility contains Jupyter notebooks and R Markdown files that are used to create the figures and tables in the manuscript.
Please feel free to open an issue for bug reports, change requests, or other contributions.
Packaged with: Flit