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

JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions 2023 (410) JMIR Theme Issue: COVID-19 Special Issue (2562) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1545) Outbreak and Pandemic Preparedness and Management (1844) Natural Language Processing (945) Machine Learning (2204) Artificial Intelligence (2313)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40899, first published .
Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study

Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study

Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study

Authors of this article:

Rachel Weger1 Author Orcid Image ;   Juan Antonio Lossio-Ventura2 Author Orcid Image ;   Margaret Rose-McCandlish1 Author Orcid Image ;   Jacob S Shaw2 Author Orcid Image ;   Stephen Sinclair2 Author Orcid Image ;   Francisco Pereira2 Author Orcid Image ;   Joyce Y Chung2 Author Orcid Image ;   Lauren Yvette Atlas1, 2, 3 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Lossio-Ventura J, Weger R, Lee A, Guinee E, Chung J, Atlas L, Linos E, Pereira F. A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data. JMIR Mental Health 2024;11:e50150 View
  2. Sweeney C, Ennis E, Mulvenna M, Bond R, O'Neill S. Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review. JMIR Mental Health 2024;11:e55747 View
  3. Gifkins J, Troth A, Loudoun R, Johnston A. A mixed method approach to how shiftworking emergency department (ED) nurses reduce the effects of fatigue and differences in strategies between those with varying levels of fatigue. Collegian 2024;31(5):277 View
  4. Atlas L, Farmer C, Shaw J, Gibbons A, Guinee E, Lossio-Ventura J, Ballard E, Ernst M, Japee S, Pereira F, Chung J. Dynamic effects of psychiatric vulnerability, loneliness and isolation on distress during the first year of the COVID-19 pandemic. Nature Mental Health 2025;3(2):199 View

Books/Policy Documents

  1. Pineda-Briseño A, Chire-Saire J, Oblitas J. Applied Machine Learning and Data Analytics. View

Conference Proceedings

  1. Khandelwal V, Gaur M, Kursuncu U, Shalin V, Sheth A. 2024 IEEE International Conference on Big Data (BigData). A Domain-Agnostic Neurosymbolic Approach for Big Social Data Analysis: Evaluating Mental Health Sentiment on Social Media during COVID-19 View