W-NUT 2020 Shared Task on Identification of informative COVID-19 English Tweets




VinAI Research is pleased to be the main organizer of the W-NUT 2020 Shared Task on Identification of informative COVID-19 English Tweets.

The goals of this shared task are:

  • To develop a language processing task that potentially impacts research and downstream applications,
  • To provide the community with a new dataset for identifying informative COVID-19 English Tweets.

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.

Important Dates

  • Data available: June 21, 2020
  • Registration closed: August 14, 2020
  • Evaluation window: August 17, 2020 – August 21, 2020
  • System description papers submitted: September 4, 2020
  • Papers reviewed: September 25, 2020
  • Papers camera ready: October 08, 2020
  • Workshop day: November 19, 2020

? WEBSITE: http://noisy-text.github.io/2020/covid19tweet-task.html
? REGISTER: https://forms.gle/TEFbySkQoPCJzs8H6

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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