Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33110, first published .
Exploring Resource-Sharing Behaviors for Finding Relevant Health Resources: Analysis of an Online Ovarian Cancer Community

Exploring Resource-Sharing Behaviors for Finding Relevant Health Resources: Analysis of an Online Ovarian Cancer Community

Exploring Resource-Sharing Behaviors for Finding Relevant Health Resources: Analysis of an Online Ovarian Cancer Community

Journals

  1. Chi Y, Thaker K, He D, Hui V, Donovan H, Brusilovsky P, Lee Y. Knowledge Acquisition and Social Support in Online Health Communities: Analysis of an Online Ovarian Cancer Community. JMIR Cancer 2022;8(3):e39643 View
  2. Zou N, Thaker K, He D. A Preliminary Study of Ovarian Cancer Caregivers’ Health Information Seeking on Social Media. Proceedings of the Association for Information Science and Technology 2023;60(1):1230 View
  3. Chi Y, Hui V, Kunsak H, Brusilovsky P, Donovan H, He D, Lee Y. Women with ovarian cancer’s information seeking and avoidance behaviors: an interview study. JAMIA Open 2024;7(1) View
  4. Zhao J, Zhu D, Chang F, Han T. Rehab-Diary: Enhancing Recovery Identity with an Online Support Group for Middle Aged and Older Ovarian Cancer Patients. Proceedings of the ACM on Human-Computer Interaction 2024;8(MHCI):1 View

Conference Proceedings

  1. Rahdari B, Brusilovsky P, He D, Thaker K, Luo Z, Lee Y. Proceedings of the 16th ACM Conference on Recommender Systems. HELPeR: An Interactive Recommender System for Ovarian Cancer Patients and Caregivers View
  2. Thaker K. Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. KA-Recsys: Patient Focused Knowledge Appropriate Health Recommender System View
  3. Zou N, Ji Y, Xie B, He D, Luo Z. Proceedings of the 2023 Conference on Human Information Interaction and Retrieval. Mapping dementia caregivers’ comments on social media with evidence-based care strategies for memory loss and confusion View
  4. Thaker K. Proceedings of the 16th ACM Conference on Recommender Systems. KA-Recsys: Knowledge Appropriate Patient Focused Recommendation Technologies View