IIITBH at WNUT-2020 Task 2: Exploiting the best of both worlds

Saichethan Reddy, Pradeep Biswal


Abstract
In this paper, we present IIITBH team’s effort to solve the second shared task of the 6th Workshop on Noisy User-generated Text (W-NUT)i.e Identification of informative COVID-19 English Tweets. The central theme of the task is to develop a system that automatically identify whether an English Tweet related to the novel coronavirus (COVID-19) is Informative or not. Our approach is based on exploiting semantic information from both max pooling and average pooling, to this end we propose two models.
Anthology ID:
2020.wnut-1.46
Volume:
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)
Month:
November
Year:
2020
Address:
Online
Editors:
Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
342–346
Language:
URL:
https://aclanthology.org/2020.wnut-1.46
DOI:
10.18653/v1/2020.wnut-1.46
Bibkey:
Cite (ACL):
Saichethan Reddy and Pradeep Biswal. 2020. IIITBH at WNUT-2020 Task 2: Exploiting the best of both worlds. In Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), pages 342–346, Online. Association for Computational Linguistics.
Cite (Informal):
IIITBH at WNUT-2020 Task 2: Exploiting the best of both worlds (Reddy & Biswal, WNUT 2020)
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PDF:
https://aclanthology.org/2020.wnut-1.46.pdf