Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets

Reem Suwaileh, Muhammad Imran, Tamer Elsayed, Hassan Sajjad


Abstract
The widespread usage of Twitter during emergencies has provided a new opportunity and timely resource to crisis responders for various disaster management tasks. Geolocation information of pertinent tweets is crucial for gaining situational awareness and delivering aid. However, the majority of tweets do not come with geoinformation. In this work, we focus on the task of location mention recognition from crisis-related tweets. Specifically, we investigate the influence of different types of labeled training data on the performance of a BERT-based classification model. We explore several training settings such as combing in- and out-domain data from news articles and general-purpose and crisis-related tweets. Furthermore, we investigate the effect of geospatial proximity while training on near or far-away events from the target event. Using five different datasets, our extensive experiments provide answers to several critical research questions that are useful for the research community to foster research in this important direction. For example, results show that, for training a location mention recognition model, Twitter-based data is preferred over general-purpose data; and crisis-related data is preferred over general-purpose Twitter data. Furthermore, training on data from geographically-nearby disaster events to the target event boosts the performance compared to training on distant events.
Anthology ID:
2020.coling-main.550
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
6252–6263
Language:
URL:
https://aclanthology.org/2020.coling-main.550
DOI:
10.18653/v1/2020.coling-main.550
Bibkey:
Cite (ACL):
Reem Suwaileh, Muhammad Imran, Tamer Elsayed, and Hassan Sajjad. 2020. Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6252–6263, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets (Suwaileh et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.550.pdf
Data
CoNLL-2003