Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59794, first published .
Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Journals

  1. Gardasevic S, Jaiswal A, Lamba M, Funakoshi J, Chu K, Shah A, Sun Y, Pokhrel P, Washington P. Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review. Information 2024;15(11):690 View
  2. Zhang Y, Wang J, Zong H, Singla R, Ullah A, Liu X, Wu R, Ren S, Shen B. The comprehensive clinical benefits of digital phenotyping: from broad adoption to full impact. npj Digital Medicine 2025;8(1) View
  3. Otero P, Menéndez-Blázquez J, March D. Challenges of passive citizen science in ecology within a shifting social media landscape. Ecological Informatics 2025;90:103278 View
  4. Bulusu A, Cotran P, Alwreikat A, Jiang Y, Cooper M, Ramsey K, Verghese A, Ramsey D. Evaluation of Glaucoma Treatment Information on Social Media Using Large Language Models. Journal of Glaucoma 2026;35(3):173 View

Books/Policy Documents

  1. Mittal S, Chandel A, Nguyen P. Improving Entrepreneurial Processes Through Advanced AI. View
  2. Chambers S, Kelley M. Artificial Intelligence in Education. View
  3. Chao C, Hsu P, Wei X, See T. Multidisciplinary Social Networks Research. View
  4. Marwala T. The Governance of Artificial Intelligence. View

Conference Proceedings

  1. Qian Y, Kargarandehkordi A, Sun Y, Azizian P, Mutlu O, Surabhi S, Jabbar Z, Wall D, Washington P, Chen H. 2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Hashtag2Action: Data Engineering and Self-Supervised Pre-Training for Action Recognition in Short-Form Videos View