Speech acts and Communicative Intentions for Urgency Detection

Laurenti Enzo, Bourgon Nils, Farah Benamara, Mari Alda, Véronique Moriceau, Courgeon Camille


Abstract
Recognizing speech acts (SA) is crucial for capturing meaning beyond what is said, making communicative intentions particularly relevant to identify urgent messages. This paper attempts to measure for the first time the impact of SA on urgency detection during crises,006in tweets. We propose a new dataset annotated for both urgency and SA, and develop several deep learning architectures to inject SA into urgency detection while ensuring models generalisability. Our results show that taking speech acts into account in tweet analysis improves information type detection in an out-of-type configuration where models are evaluated in unseen event types during training. These results are encouraging and constitute a first step towards SA-aware disaster management in social media.
Anthology ID:
2022.starsem-1.25
Volume:
Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
Month:
July
Year:
2022
Address:
Seattle, Washington
Editors:
Vivi Nastase, Ellie Pavlick, Mohammad Taher Pilehvar, Jose Camacho-Collados, Alessandro Raganato
Venue:
*SEM
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
289–298
Language:
URL:
https://aclanthology.org/2022.starsem-1.25
DOI:
10.18653/v1/2022.starsem-1.25
Bibkey:
Cite (ACL):
Laurenti Enzo, Bourgon Nils, Farah Benamara, Mari Alda, Véronique Moriceau, and Courgeon Camille. 2022. Speech acts and Communicative Intentions for Urgency Detection. In Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, pages 289–298, Seattle, Washington. Association for Computational Linguistics.
Cite (Informal):
Speech acts and Communicative Intentions for Urgency Detection (Enzo et al., *SEM 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.starsem-1.25.pdf