InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction

Hettiarachchi, Hansi and Ranasinghe, Tharindu (2020) InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction. In: 6th Workshop on Noisy User-generated Text (W-NUT 2020), 30th November 2020, Online.

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Official URL: https://aclanthology.org/2020.wnut-1.49/

Abstract

Identifying informative tweets is an important step when building information extraction systems based on social media. WNUT-2020 Task 2 was organised to recognise informative tweets from noise tweets. In this paper, we present our approach to tackle the task objective using transformers. Overall, our approach achieves 10th place in the final rankings scoring 0.9004 F1 score for the test set.

Item Type:	Conference or Workshop Item (Paper)
Identification Number:	10.18653/v1/2020.wnut-1.49
Dates:	Date Event 29 September 2020 Accepted 19 November 2020 Published
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Hansi Hettiarachchi
Date Deposited:	21 Dec 2021 15:12
Last Modified:	21 Dec 2021 15:13
URI:	https://www.open-access.bcu.ac.uk/id/eprint/12557