2020 EMNLP EMNLP 2020

Emory at WNUT-2020 Task 2: Combining Pretrained Deep Learning Models and Feature Enrichment for Informative Tweet Identification

Abstract

AbstractThis paper describes the system developed by the Emory team for the WNUT-2020 Task 2: “Identifi- cation of Informative COVID-19 English Tweet”. Our system explores three recent Transformer- based deep learning models pretrained on large- scale data to encode documents. Moreover, we developed two feature enrichment methods to en- hance document embeddings by integrating emoji embeddings and syntactic features into deep learn- ing models. Our system achieved F1-score of 0.897 and accuracy of 90.1% on the test set, and ranked in the top-third of all 55 teams.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio