This repository hosts the code for the paper:
GeneticPrism: Multifaceted Visualization of Citation-based Scholarly Research Evolution

🔗 Online System: https://genetic-flow.com / https://geneticflow.ye-sun.com/

🎞️ Demo Video: https://youtu.be/zVbM7lgA6Ig

See User Manual and Appendix in Wiki pages.

Understanding the evolution of scholarly research is essential for academic decision-making (e.g., research planning and frontier exploration). Existing platforms like Google Scholar rely on abstract numerical indicators lacking contextual depth, while visualization approaches rarely leverage curated self-citation data to depict individual scholars’ evolution.

This work introduces:

• A 3D prism metaphor visualizing scholars’ research profiles
• A scroll metaphor visualizing structured topic evolution via streamgraphs and inter-topic flow maps
• Six-degree-impact glyphs highlighting interdisciplinary breakthroughs
• Evaluations through case studies (Turing Award laureates, visualization venues) and user studies

Processed from the open-source Academic Graph:

• v1 (up to Sept. 2022): process Microsoft Academic Graph (MAG) to construct GF Graph (from KDD’23 paper, github repo)
• v2 (up to Oct. 2024): MAG fused with OpenAlex

🔗 Download v2 dataset: Hugging Face​. Due to the dataset's size, it is divided into two compressed archives.

• The ​csv.tar.gz​ contains CSV files covering all research fields ​except Artificial Intelligence (AI)​. After extraction, place these CSV files directly in your ​project root directory.
• The ​AI.tar.gz​ contains ​only AI-related data​ – extract its CSV files into the project's ​csv/.

The system remains fully functional if only one archive (either AI or Non-AI) is installed, enabling flexible data management based on research needs.

Place the extracted CSV files in the project root directory. The directory structure should look like this:

GeneticPrism/
├── csv/
│   ├── AI/  # Contains AI-related data
│   │   ├── links/
│   │   ├── papers/
│   │   ├── paperIDDistribution.csv
│   │   ├── top_field_authors.csv
│   │   └── field_leaves.csv
│   └── <field>     # Contains other research fields
│       ├── links/
│       ├── papers/
│       └── ...
├── manage.py
└── ...

conda create -n GFVis python=3.11
conda activate GFVis
pip install -r requirements.txt

Option A: Direct run

python manage.py runserver 0.0.0.0:9001

Option B: Background run (persistent)

nohup python manage.py runserver 0.0.0.0:9001 2>&1 &

• Access the system at: http://<your-ip>:9001
• Use ctrl + c to terminate direct runs
• Monitor background processes via tail -f nohup.out