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SIGNLENS

SIGNLENS is a tool that helps to analyze polarized social relationships based on signed graph modeling.

It also include a Python package for signed graph modeling.

System Design

The illustration of the proposed SIGNLENS.

Individual Analysis

For individual analysis, we usually focus on some specific nodes.

Group Analysis

For group analysis, we analyze it with time.

Data Collection

We give two examples from real-world applications to demonstrate how our system works.

Here is the cleaned data link

The China Biographical Database (CBDB)

The data is collected from CBDB

Run the spider by:

python get_cbdb_data.py

United States Congress Vote (UCSV)

The data is collected from GovTrack.us

Run the spider by:

python get_govtrack_data.py

Data Analysis

CBDB

For CBDB dataset, you can follow this jupyter notebook

CBDB

USCV

For USCV dataset, you can follow this jupyter notebook

House
Senate

Developments

This system is a web based system but also include a Python Package sign_lens. This readme will help you to run it.

Some codes will be updated after the busy weeks. Sorry for the delay!

Cite

Please cite `our paper <https://ojs.aaai.org/index.php/ICWSM/article/view/18136`_ if you use these codes and datasets in your own work:

@inproceedings{huang2021signlens,
  title={SIGNLENS: A Tool for Analyzing People's Polarization Social Relationship Based on Signed Graph Modeling},
  author={Huang, Junjie and Shen, Huawei and Cheng, Xueqi},
  booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
  volume={15},
  pages={1091--1093},
  year={2021}
}

Feel free to email us if you wish to improve this project