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

JMIR Theme Issue: COVID-19 Special Issue (2278) Outbreak and Pandemic Preparedness and Management (1561) Infodemiology and Infoveillance (1167) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (946) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1455) New Methods (800)

Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41517, first published .
Sentiment Analysis of Insomnia-Related Tweets via a Combination of Transformers Using Dempster-Shafer Theory: Pre– and Peri–COVID-19 Pandemic Retrospective Study

Sentiment Analysis of Insomnia-Related Tweets via a Combination of Transformers Using Dempster-Shafer Theory: Pre– and Peri–COVID-19 Pandemic Retrospective Study

Sentiment Analysis of Insomnia-Related Tweets via a Combination of Transformers Using Dempster-Shafer Theory: Pre– and Peri–COVID-19 Pandemic Retrospective Study

Authors of this article:

Arash Maghsoudi 1 Author Orcid Image ;   Sara Nowakowski 1 Author Orcid Image ;   Ritwick Agrawal 1 Author Orcid Image ;   Amir Sharafkhaneh 1 Author Orcid Image ;   Mark E Kunik 1 Author Orcid Image ;   Aanand D Naik 2 Author Orcid Image ;   Hua Xu 3 Author Orcid Image ;   Javad Razjouyan 1 Author Orcid Image
Article Authors Cited by (2) Tweetations (10) Metrics

Journals

  1. Tan K, Lee C, Lim K. A Survey of Sentiment Analysis: Approaches, Datasets, and Future Research. Applied Sciences 2023;13(7):4550 View
  2. Swanson K, Ravi A, Saleh S, Weia B, Pleasants E, Arvisais-Anhalt S. Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis. Journal of Medical Internet Research 2023;25:e46655 View