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

Peer-to-Peer Support and Online Communities (628) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1618) Depression and Mood Disorders; Suicide Prevention (1339)

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

This is a member publication of UC Davis - Shields Library, Davis, CA, USA

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17365, first published .
Examining Social Capital, Social Support, and Language Use in an Online Depression Forum: Social Network and Content Analysis

Examining Social Capital, Social Support, and Language Use in an Online Depression Forum: Social Network and Content Analysis

Examining Social Capital, Social Support, and Language Use in an Online Depression Forum: Social Network and Content Analysis

Authors of this article:

Wenjing Pan1 Author Orcid Image ;   Bo Feng2 Author Orcid Image ;   Cuihua Shen2 Author Orcid Image
Article Authors Cited by (18) Tweetations (3) Metrics

Journals

  1. Ramamoorthy T, Karmegam D, Mappillairaju B. Use of social media data for disease based social network analysis and network modeling: A Systematic Review. Informatics for Health and Social Care 2021;46(4):443 View
  2. Xin W. Lack of alternative: Chinese first-time mothers’ construction of social support network of online secondary groups. DIGITAL HEALTH 2022;8:205520762211290 View
  3. Dashtian H, Murthy D, Kong G. An Exploration of e-Cigarette–Related Search Items on YouTube: Network Analysis. Journal of Medical Internet Research 2022;24(1):e30679 View
  4. Liu Y, Huang W, Luo D. The reception of support in peer-to-peer online networks: Network position, support solicitation, and support provision in an online asthma caregivers group. Health Informatics Journal 2022;28(1) View
  5. Luo C, Chen A, Cui B, Liao W. Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China. Telematics and Informatics 2021;65:101712 View
  6. Bizzotto N, Morlino S, Schulz P. Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study. JMIR Research Protocols 2022;11(5):e35347 View
  7. Liu Y, Yin Z, Wan Z, Yan C, Xia W, Ni C, Clayton E, Vorobeychik Y, Kantarcioglu M, Malin B. Implicit Incentives Among Reddit Users to Prioritize Attention Over Privacy and Reveal Their Faces When Discussing Direct-to-Consumer Genetic Test Results: Topic and Attention Analysis. JMIR Infodemiology 2022;2(2):e35702 View
  8. Smit D, Vrijsen J, Broekman T, Groeneweg B, Spijker J. User Engagement Within an Online Peer Support Community (Depression Connect) and Recovery-Related Changes in Empowerment: Longitudinal User Survey. JMIR Formative Research 2022;6(11):e39912 View
  9. Shi J, Khoo Z. Online health community for change: Analysis of self-disclosure and social networks of users with depression. Frontiers in Psychology 2023;14 View
  10. Zhang Z, Mu H, Huang S. Playing to Save Sisters: How Female Gaming Communities Foster Social Support within Different Cultural Contexts. Journal of Broadcasting & Electronic Media 2023;67(5):693 View
  11. Wu M, Long R, Chen H, Li W. The spatial difference of multi-layer climate change information flow and network construction: A comparison of “dual carbon” scenarios. Journal of Cleaner Production 2023;414:137591 View
  12. Shi J, Khoo Z. Words for the hearts: a corpus study of metaphors in online depression communities. Frontiers in Psychology 2023;14 View
  13. Talbot A, Ford T, Ryan S, Mahtani K, Albury C. #TreatmentResistantDepression: A qualitative content analysis of Tweets about difficult‐to‐treat depression. Health Expectations 2023;26(5):1986 View
  14. Adams N. A Triad of Physical Masculinities: Examining Multiple ‘Hegemonic’ Bodybuilding Identities in Anabolic-Androgenic Steroid (AAS) Online Discussion Groups. Deviant Behavior 2023;44(10):1498 View
  15. Zhang Z. Fight against hair loss together: exploring self-disclosure and social support in an online hair loss support community. Online Information Review 2024;48(5):841 View
  16. Jing Y, Jiang G. “No man is an island”: How Chinese netizens use deliberate metaphors to provide “depression sufferers” with social support. DIGITAL HEALTH 2024;10 View
  17. Wu X, Zhou Y, Zhong B. Measuring social support for depression on social media: A multifaceted study on user interaction and emotional spread. Telematics and Informatics 2024;89:102120 View
  18. Lin Y, Li S. Searching for Love and Babies: A Qualitative Study on Online Social Support Among Women with Infertility. Health Communication 2024:1 View