Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28648, first published .
Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study

Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study

Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study

Journals

  1. M. D, S. S. A machine learning approach on analysing the sentiments in the adoption of telemedicine application during COVID-19. Journal of Science and Technology Policy Management 2024;15(4):725 View
  2. Gozuacik N, Sakar C, Ozcan S. Technological forecasting based on estimation of word embedding matrix using LSTM networks. Technological Forecasting and Social Change 2023;191:122520 View
  3. Shoults C, Dawson L, Hayes C, Eswaran H. Comparing the Discussion of Telehealth in Two Social Media Platforms: Social Listening Analysis. Telemedicine Reports 2023;4(1):236 View
  4. Jensen R, Rohde J, Muro A, Schweppe C, Vanderpool R. Analysis of Telehealth Discussion Trends on Reddit (2019–2022). Telemedicine and e-Health 2024;30(6):e1790 View
  5. Nugroho A, Pitaloka A. PHYSICIANS AND DISRUPTION ON TELEMEDICINE: A SYSTEMATIC LITERATURE REVIEW. Jurnal Administrasi Kesehatan Indonesia 2023;11(2):244 View

Books/Policy Documents

  1. Concoff A. Telerheumatology. View