The goals of this shared task are: (1) To develop a language processing task that potentially impacts research and downstream applications, and (2) To provide the community with a new dataset for identifying informative COVID-19 EnglishTweets. We believe systems developed for this shared task will be beneficial for the development of COVID-19 related monitoring systems.
Creators of systems with valid results that are submitted to this shared task are invited to send a short paper (4 pages plus references) to the W-NUT 2020 workshop at EMNLP 2020, which describes the system. Paper submissions of systems and system descriptions will be published in Proceedings of W-NUT 2020 in the ACL Anthology.
REGISTER: https://forms.gle/TEFbySkQoPCJzs8H6 WEBSITE: http://noisy-text.github.io/2020/covid19tweet-task.html Codalab submission page: https://competitions.codalab.org/competitions/25845
The EMNLP-2020's W-NUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays. Please find more details about W-NUT 2020 at http://noisy-text.github.io/2020.
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