In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives. From the spatial perspective, our goal here is to get a first estimation of the quality and precision of the geographical information featured in the collected corpus. From a topical perspective, we discuss the representation of Twitter posts, and strategies to process an initially unlabeled corpus of tweets.
@article{arxiv.1903.04748,
title = {Extracting localized information from a Twitter corpus for flood prevention},
author = {Etienne Brangbour and Pierrick Bruneau and Stéphane Marchand-Maillet and Renaud Hostache and Patrick Matgen and Marco Chini and Thomas Tamisier},
journal= {arXiv preprint arXiv:1903.04748},
year = {2019}
}