Note: It seems tensorflow-gpu 2.0.0a0
cannot download now. I plan to re-write the code to adapt it to the latest TensorFlow version.
This repo provides a reference implementation of CasFlow as described in the paper:
CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction
Xovee Xu, Fan Zhou, Kunpeng Zhang, Siyuan Liu, and Goce Trajcevski
IEEE Transactions on Knowledge and Data Engineering (TKDE), 14 pages, 2021
The code was tested with python 3.7
, tensorflow-gpu 2.0.0a
, cudatookkit 10.0
, and cudnn 7.6.5
. Install the dependencies via Anaconda:
# create virtual environment
conda create --name casflow python=3.7 cudatoolkit=10.0 cudnn=7.6.5
# activate environment
conda activate casflow
# install other requirements
pip install -r requirements.txt
cd ./casflow
# generate information cascades
python gene_cas.py --input=./dataset/weibo/
# generate cascade graph and global graph embeddings
python gene_emb.py --input=./dataset/weibo/
# run CasFlow model
python casflow.py --input=./dataset/weibo/
More running options are described in the codes, e.g., --input=./dataset/weibo/
See some sample cascades in ./dataset/sample/
.
Datasets download link: Google Drive or Baidu Drive (password: 1msd
).
The datasets we used in the paper are come from:
- Twitter (Weng et al., Virality Prediction and Community Structure in Social Network, Scientific Report, 2013).
- Weibo (Cao et al., DeepHawkes: Bridging the Gap between Prediction and Understanding of Information Cascades, CIKM, 2017). You can also download Weibo dataset here in Google Drive.
- APS (Released by American Physical Society, obtained at Jan 17, 2019).
If you find CasFlow useful for your research, please consider citing us 😘:
@article{xu2021casflow,
author = {Xovee Xu and Fan Zhou and Kunpeng Zhang and Siyuan Liu and Goce Trajcevski},
title = {Cas{F}low: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction},
journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
year = {2021},
numpages = {14},
doi = {10.1109/TKDE.2021.3126475},
}
This paper is an extension of VaCas:
@inproceedings{zhou2020variational,
author = {Fan Zhou and Xovee Xu and Kunpeng Zhang and Goce Trajcevski and Ting Zhong},
title = {Variational Information Diffusion for Probabilistic Cascades Prediction},
booktitle = {IEEE International Conference on Computer Communications (INFOCOM)},
year = {2020},
pages = {1618--1627},
doi = {10.1109/INFOCOM41043.2020.9155359},
}
We also have a survey paper you might be interested:
@article{zhou2021survey,
author = {Fan Zhou and Xovee Xu and Goce Trajcevski and Kunpeng Zhang},
title = {A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances},
journal = {ACM Computing Surveys (CSUR)},
volume = {54},
number = {2},
year = {2021},
articleno = {27},
numpages = {36},
doi = {10.1145/3433000},
}
For any questions please open an issue or drop an email to: xovee at ieee.org