This paper is in the following e-collection/theme issue:

Research Letter (37) Natural Language Processing (693) Advanced Data Analytics in eHealth (133) Artificial Intelligence (1371)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46484, first published .
Automatically Identifying Self-Reports of COVID-19 Diagnosis on Twitter: An Annotated Data Set, Deep Neural Network Classifiers, and a Large-Scale Cohort

Automatically Identifying Self-Reports of COVID-19 Diagnosis on Twitter: An Annotated Data Set, Deep Neural Network Classifiers, and a Large-Scale Cohort

Automatically Identifying Self-Reports of COVID-19 Diagnosis on Twitter: An Annotated Data Set, Deep Neural Network Classifiers, and a Large-Scale Cohort

Authors of this article:

Ari Z Klein1 Author Orcid Image ;   Shriya Kunatharaju2 Author Orcid Image ;   Karen O'Connor1 Author Orcid Image ;   Graciela Gonzalez-Hernandez3 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Almasoud A, Alshahrani H, Hassan A, Almalki N, Motwakel A. Modified Aquila Optimizer with Stacked Deep Learning-Based Sentiment Analysis of COVID-19 Tweets. Electronics 2023;12(19):4125 View
  2. Klein A, Banda J, Guo Y, Schmidt A, Xu D, Flores Amaro I, Rodriguez-Esteban R, Sarker A, Gonzalez-Hernandez G. Overview of the 8th Social Media Mining for Health Applications (#SMM4H) shared tasks at the AMIA 2023 Annual Symposium. Journal of the American Medical Informatics Association 2024;31(4):991 View

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  1. Jiang Y, Qiu R, Zhang Y, Zhang P. Databases Theory and Applications. View