casflow
casflow copied to clipboard
TKDE 2021. CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction.
CasFlow
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), 2021
Basic Usage
Requirements
The code was tested with python 3.9.7
, tensorflow 2.9.1
, cudatoolkit 11.2
, and cudnn 8.1.0
. Install the dependencies via Anaconda:
# create virtual environment
conda create --name casflow python=3.9
# activate environment
conda activate casflow
# install tensorflow and other requirements
conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
pip install -r requirements.txt
Run the code
cd ./casflow
# generate information cascades
python gene_cas.py --input=./dataset/sample/
# generate cascade graph and global graph embeddings
python gene_emb.py --input=./dataset/sample/
# run CasFlow model
python casflow.py --input=./dataset/sample/
More running options are described in the codes, e.g.,
- Using the Weibo dataset:
--input=./dataset/weibo/
- Change observation time:
--observation_time=3600
Datasets
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).
Cite
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},
volume = {35},
number = {4},
pages={3484-3499},
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},
volume = {54},
number = {2},
year = {2021},
articleno = {27},
numpages = {36},
doi = {10.1145/3433000},
}
Contact
For any questions please open an issue or drop an email to: xovee at live.com