Skip to content

smacawi/tweet-classifier

Repository files navigation

Using deep learning and social network analysis to understand and manage extreme flooding

Code for Using deep learning and social network analysis to understand and manage extreme flooding published in the Journal of Contingencies and Crisis Management.

SNA

For more information on the social network analysis, see https://smacawi.github.io/social-network-analysis-report.pdf

Citation

@article{romascanu2020using,
  title={Using deep learning and social network analysis to understand and manage extreme flooding},
  author={Romascanu, Andrei and Ker, Hannah and Sieber, Renee and Greenidge, Sarah and Lumley, Sam and Bush, Drew and Morgan, Stefan and Zhao, Rosie and Brunila, Mikael},
  journal={Journal of Contingencies and Crisis Management},
  volume={28},
  number={3},
  pages={251--261},
  year={2020},
  doi={https://doi.org/10.1111/1468-5973.12311},
  publisher={Wiley Online Library}
}

About

Training deep learning models to classify disaster-related tweets in the context of crisis management. Published as "Using deep learning and social network analysis to understand and manage extreme flooding" in Journal of Contingencies and Crisis Management

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages