What makes an online help-seeking message go far during the COVID-19 crisis in mainland China? A multilevel regression analysis
- PMID: 35340906
- PMCID: PMC8942799
- DOI: 10.1177/20552076221085061
What makes an online help-seeking message go far during the COVID-19 crisis in mainland China? A multilevel regression analysis
Abstract
Various studies have explored the underlying mechanisms that enhance the overall reach of a support-seeking message on social media networks. However, little attention has been paid to an under-examined structural feature of help-seeking message diffusion, information diffusion depth, and how support-seeking messages can traverse vertically into social media networks to reach other users who are not directly connected to the help-seeker. Using the multilevel regression to analyze 705 help-seeking posts regarding COVID-19 on Sina Weibo, we examined sender, content, and environmental factors to investigate what makes help-seeking messages traverse deeply into social media networks. Results suggested that bandwagon cues, anger, instrumental appeal, and intermediate self-disclosure facilitate the diffusion depth of help-seeking messages. However, the effects of these factors were moderated by the epidemic severity. Implications of the findings on support-seeking behavior and narrative strategies on social media were also discussed.
Keywords: COVID-19; depth; help-seeking; heuristic-systematic model; information diffusion.
© The Author(s) 2022.
Conflict of interest statement
Conflict of interest :The authors have no conflicts of interest to declare.
Figures
References
-
- World Health Organization (WHO). Coronavirus disease (COVID-19) pandemic. Available at: https://covid19.who.int/ (2022, assessed 27 January 2022).
-
- Weibo. Weibo Pneumonia patients help-seeking forum. Retrieved from https://weibo.com/p/1008084882401a015244a2ab18ee43f7772d6f/super_index?c... (2020, assessed 21 July 2020).
-
- Im E-O, Chee W. The use of internet cancer support groups by ethnic minorities. J Transcult Nurs 2008; 19: 74–82. - PubMed
-
- Shaw BR, Hawkins R, Arora Net al. et al. An exploratory study of predictors of participation in a computer support group for women with breast cancer. Comput Inform Nursing 2006; 24: 18–27. - PubMed
LinkOut - more resources
Full Text Sources
