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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1666) Infodemiology and Infoveillance (1369) Anxiety and Stress Disorders (1081)

Published on in Vol 3, No 2 (2017): Apr-Jun

How Do You #relax When You’re #stressed? A Content Analysis and Infodemiology Study of Stress-Related Tweets

How Do You #relax When You’re #stressed? A Content Analysis and Infodemiology Study of Stress-Related Tweets

How Do You #relax When You’re #stressed? A Content Analysis and Infodemiology Study of Stress-Related Tweets

Authors of this article:

Son Doan1 Author Orcid Image ;   Amanda Ritchart2 Author Orcid Image ;   Nicholas Perry3 Author Orcid Image ;   Juan D Chaparro1 Author Orcid Image ;   Mike Conway4 Author Orcid Image
Article Authors Cited by (18) Tweetations (29) Metrics

Journals

  1. Brandt H, Turner-McGrievy G, Friedman D, Gentile D, Schrock C, Thomas T, West D. Examining the Role of Twitter in Response and Recovery During and After Historic Flooding in South Carolina. Journal of Public Health Management and Practice 2019;25(5):E6 View
  2. Doan S, Yang E, Tilak S, Li P, Zisook D, Torii M. Extracting health-related causality from twitter messages using natural language processing. BMC Medical Informatics and Decision Making 2019;19(S3) View
  3. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  4. Shatte A, Hutchinson D, Teague S. Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine 2019;49(09):1426 View
  5. López Seguí F, Ander Egg Aguilar R, de Maeztu G, García-Altés A, García Cuyàs F, Walsh S, Sagarra Castro M, Vidal-Alaball J. Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: The Evaluation of Text Classification Algorithms Using Supervised Machine Learning. International Journal of Environmental Research and Public Health 2020;17(3):1093 View
  6. Skaik R, Inkpen D. Using Social Media for Mental Health Surveillance. ACM Computing Surveys 2021;53(6):1 View
  7. Le Glaz A, Haralambous Y, Kim-Dufor D, Lenca P, Billot R, Ryan T, Marsh J, DeVylder J, Walter M, Berrouiguet S, Lemey C. Machine Learning and Natural Language Processing in Mental Health: Systematic Review. Journal of Medical Internet Research 2021;23(5):e15708 View
  8. Miller M, Romine W, Oroszi T. Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events. JMIR Public Health and Surveillance 2021;7(6):e27976 View
  9. Ahne A, Khetan V, Tannier X, Rizvi M, Czernichow T, Orchard F, Bour C, Fano A, Fagherazzi G. Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach. JMIR Medical Informatics 2022;10(7):e37201 View
  10. Shakeri Hossein Abad Z, Butler G, Thompson W, Lee J. Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research. JMIR Public Health and Surveillance 2022;8(2):e32355 View
  11. Lim J, Lee S, Noh J, Lee W, Su P, Yoon Y. Effectiveness of Mental Health Care by Using Machine Learning on Manufacturing Worker. International Journal of Precision Engineering and Manufacturing-Smart Technology 2023;1(2):227 View
  12. Brassel S, Brunner M, Campbell A, Power E, Togher L. Exploring Discussions About Virtual Reality on Twitter to Inform Brain Injury Rehabilitation: Content and Network Analysis. Journal of Medical Internet Research 2024;26:e45168 View
  13. Wang J, Jin X. Commentary: Psychometric properties of the modified Suicide Stroop Task (M-SST) in patients with suicide risk and healthy controls. Frontiers in Psychology 2024;15 View

Books/Policy Documents

  1. Amrani G, Khennou F, Chaoui N. Information and Software Technologies. View