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

Infodemiology and Infoveillance (1270) Occupational Health and Ergonomics/Prevention at the Workplace (220) Policy (51) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010)

Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18181, first published .
Exploring Public Awareness of Overwork Prevention With Big Data From Google Trends: Retrospective Analysis

Exploring Public Awareness of Overwork Prevention With Big Data From Google Trends: Retrospective Analysis

Exploring Public Awareness of Overwork Prevention With Big Data From Google Trends: Retrospective Analysis

Authors of this article:

Ro-Ting Lin1 Author Orcid Image ;   Yawen Cheng2 Author Orcid Image ;   Yan-Cheng Jiang1 Author Orcid Image
Article Authors Cited by (7) Tweetations (3) Metrics

Journals

  1. Tu B, Wei L, Jia Y, Qian J. Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index. BMC Infectious Diseases 2021;21(1) View
  2. Braunack-Mayer A, Fabrianesi B, Street J, O'Shaughnessy P, Carter S, Engelen L, Carolan L, Bosward R, Roder D, Sproston K. Sharing Government Health Data With the Private Sector: Community Attitudes Survey. Journal of Medical Internet Research 2021;23(10):e24200 View
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  5. Karatas M, Eriskin L, Deveci M, Pamucar D, Garg H. Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives. Expert Systems with Applications 2022;200:116912 View
  6. Hagiya H, Koyama T, Otsuka F. Impact of the cervical cancer awareness months on public interest in Japan: A Google Trends analysis, 2012–2021. Scientific Reports 2022;12(1) View
  7. Fang Z, Chen C. A collaborative trend prediction method using the crowdsourced wisdom of web search engines. Data Technologies and Applications 2022;56(5):741 View