WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets
Dat Quoc Nguyen, Thanh Vu, Afshin Rahimi, Mai Hoang Dao, Linh The Nguyen, Long Doan
Abstract
In this paper, we provide an overview of the WNUT-2020 shared task on the identification of informative COVID-19 English Tweets. We describe how we construct a corpus of 10K Tweets and organize the development and evaluation phases for this task. In addition, we also present a brief summary of results obtained from the final system evaluation submissions of 55 teams, finding that (i) many systems obtain very high performance, up to 0.91 F 1 score, (ii) the majority of the submissions achieve substantially higher results than the baseline fastText
Topics & Concepts
Computer scienceTask (project management)Identification (biology)Coronavirus disease 2019 (COVID-19)Natural language processingBaseline (sea)Construct (python library)Artificial intelligenceF1 scoreMachine learningPathologyBiologyDiseaseEconomicsOceanographyProgramming languageInfectious disease (medical specialty)BotanyMedicineGeologyManagementTopic ModelingNatural Language Processing TechniquesSpeech Recognition and Synthesis