TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks

Ruofan Hu, Dongyu Zhang, Dandan Tao, Thomas Hartvigsen, Hao Feng, Elke Rundensteiner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Foodborne illness is a serious but preventable public health problem - with delays in detecting the associated outbreaks resulting in productivity loss, expensive recalls, public safety hazards, and even loss of life. While social media is a promising source for identifying unreported foodborne illnesses, there is a dearth of labeled datasets for developing effective outbreak detection models. To accelerate the development of machine learning-based models for foodborne outbreak detection, we thus present TWEET-FID (TWEET-Foodborne Illness Detection), the first publicly available annotated dataset for multiple foodborne illness incident detection tasks. TWEET-FID collected from Twitter is annotated with three facets: tweet class, entity type, and slot type, with labels produced by experts as well as by crowdsource workers. We introduce several domain tasks leveraging these three facets: text relevance classification (TRC), entity mention detection (EMD), and slot filling (SF). We describe the end-to-end methodology for dataset design, creation, and labeling for supporting model development for these tasks. A comprehensive set of results for these tasks leveraging state-of-the-art single- and multi-task deep learning methods on the TWEET-FID dataset are provided. This dataset opens opportunities for future research in foodborne outbreak detection.

Original languageEnglish (US)
Title of host publication2022 Language Resources and Evaluation Conference, LREC 2022
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Pages6212-6222
Number of pages11
ISBN (Electronic)9791095546726
StatePublished - 2022
Event13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
Duration: Jun 20 2022Jun 25 2022

Publication series

Name2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Country/TerritoryFrance
CityMarseille
Period6/20/226/25/22

Keywords

  • Crowdsourcing
  • Dataset
  • Foodborne Illness Detecion
  • Multi-task Learning
  • Social Media

ASJC Scopus subject areas

  • Language and Linguistics
  • Library and Information Sciences
  • Linguistics and Language
  • Education

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