This repository contains the source code and dataset for our paper "An Efficient Automatic Meta-Path Selection for Social Event Detection via Hyperbolic Space".
- Python>=3.7
- torch>=1.4.0
- scipy>=1.2.1
- networkx>=2.4
- scikit-learn>=0.20.3
python run.py
The datasets used in GraphHAM are Kawarith[1], CrisisLexT6[2], and Twitter2012[3]. To comply with Twitter’s policies, we only uploaded the processed Kawarith dataset for demonstration. You can retrieve the complete tweet object via the dataset's link and a valid Twitter API.
All variables can be modified in config.py
If you find this repository helpful, please consider citing the following paper.
@inproceedings{qiu2024efficient,
title={An Efficient Automatic Meta-Path Selection for Social Event Detection via Hyperbolic Space},
author={Qiu, Zitai and Ma, Congbo and Wu, Jia and Yang, Jian},
booktitle={Proceedings of the ACM on Web Conference 2024},
pages={2519--2529},
year={2024}
}
[1] Alaa Alharbi and Mark Lee. 2021. Kawarith: an Arabic Twitter corpus for crisis events. In Proceedings of the Sixth Arabic Natural Language Processing Workshop. 42–52.
[2] Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Sarah Vieweg. 2014. Crisislex: A lexicon for collecting and filtering microblogged communications in crises. In Proceedings of the international AAAI conference on web and social media, Vol. 8. 376–385.
[3] Andrew J McMinn, Yashar Moshfeghi, and Joemon M Jose. 2013. Building a large-scale corpus for evaluating event detection on twitter. In Proceedings of the 22nd ACM international conference on Information & Knowledge Management. 409–418.