InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction
This work addresses the challenge of filtering relevant information from social media for information extraction systems, but it is incremental as it applies an existing method to a specific dataset.
The paper tackled the problem of identifying informative tweets about Covid-19 from noise, using a transformer-based approach, and achieved a 0.9004 F1 score, placing 10th in the WNUT-2020 Task 2 competition.
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.