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

Infoveillance and Social Listening (267) JMIR Theme Issue: COVID-19 Special Issue (2507) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1096) Infodemiology and Infoveillance (1479) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1818) Anxiety and Stress Disorders (1226)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38676, first published .
State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

Authors of this article:

Matthew P Abrams1, 2, 3 Author Orcid Image ;   Arthur P Pelullo2 Author Orcid Image ;   Zachary F Meisel1, 3, 4 Author Orcid Image ;   Raina M Merchant1, 2, 3, 4 Author Orcid Image ;   Jonathan Purtle5 Author Orcid Image ;   Anish K Agarwal1, 2, 3, 4 Author Orcid Image
Article Authors Cited by (3) Tweetations (5) Metrics

Journals

  1. Bani I, Mohamed Y, Andrade G. Evaluation of the impact of COVID-19 on stress and burnout among Ajman university (AU) medical students. Acta Psychologica 2024;246:104245 View
  2. Villanueva-Miranda I, Xie Y, Xiao G. Sentiment analysis in public health: a systematic review of the current state, challenges, and future directions. Frontiers in Public Health 2025;13 View

Books/Policy Documents

  1. Ghumman S. Demystifying Emerging Trends in Machine Learning. View