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

Infodemiology and Infoveillance (1349) Back Pain (116) Machine Learning (1465) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infoveillance and Social Listening (209) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 23, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26093, first published .
Investigating Individuals’ Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data

Investigating Individuals’ Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data

Investigating Individuals’ Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data

Authors of this article:

Robert1 ;   Pari Delir Haghighi1 Author Orcid Image ;   Frada Burstein1 Author Orcid Image ;   Donna Urquhart2 Author Orcid Image ;   Flavia Cicuttini2 Author Orcid Image
Article Authors Cited by (3) Tweetations (8) Metrics

Journals

  1. Rashid J, Kim J, Hussain A, Naseem U, Juneja S. A novel multiple kernel fuzzy topic modeling technique for biomedical data. BMC Bioinformatics 2022;23(1) View
  2. Moy A, Withall J, Hobensack M, Yeji Lee R, Levy D, Rossetti S, Rosenbloom S, Johnson K, Cato K. Eliciting Insights From Chat Logs of the 25X5 Symposium to Reduce Documentation Burden: Novel Application of Topic Modeling. Journal of Medical Internet Research 2023;25:e45645 View
  3. Issaka B, Aidoo E, Wood S, Mohammed F. “Anxiety is not cute” analysis of twitter users’ discourses on romanticizing mental illness. BMC Psychiatry 2024;24(1) View