ABSTRACT
In this paper, we present the ULD-NUIG team's system, designed as part of Social Media Mining for Health Applications (#SMM4H) Shared Task 2021. We participate in two tasks out of eight, namely "Classification of tweets self-reporting potential cases of COVID-19" (Task 5) and "Classification of COVID19 tweets containing symptoms" (Task 6). The team conduct a series of experiments to explore the challenges of both the tasks. We used a multilingual pre-trained BERT model for Task 5 and Generative Morphemes with Attention (GenMA) model for Task 6. In the experiments, we find that, GenMA, developed for Task 6, gives better results on both validation and test data-set. The submitted systems achieve F-1 score 0.53 for Task 5 and 0.84 for Task 6 on test data-set. © 2021 Association for Computational Linguistics.