Skip to content

Latest commit

 

History

History
37 lines (29 loc) · 2.08 KB

README.md

File metadata and controls

37 lines (29 loc) · 2.08 KB

DynamicGCN

This is the source code for paper Learning Dynamic Context Graphs for Predicting Social Events appeared in KDD2019 (research track)

Songgaojun Deng, Huzefa Rangwala, Yue Ning

Data

  • ICEWS event data is available online.
  • ICEWS news data has not been released publicly.（If you want to access the original news text information of the event, I suggest GDELT data.）

Libraries

Sample dataset

  • THAD6h (Thailand dynamic (temporal) dataset, around 600 nodes per graph) Google Drive
  • INDD6h Google Drive
  • EGYD6h Google Drive
  • RUSD6h Google Drive
    • *.idx / *.tidx Word index file for training/testing
    • *.x / *.tx Temporal graph input file for training/testing
    • *.y / *.ty Ground truth for training/testing

Cite

Please cite our paper if you find this code useful for your research:

@inproceedings{deng2019learning,
  title={Learning Dynamic Context Graphs for Predicting Social Events},
  author={Deng, Songgaojun and Rangwala, Huzefa and Ning, Yue},
  booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  pages={1007--1016},
  year={2019}
}