What makes an online help-seeking message go far during the COVID-19 crisis in mainland China? A multilevel regression analysis
| Autor: | Anfan Chen, Aaron Ng, Yipeng Xi, Yong Hu |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Digital Health, Vol 8 (2022) |
| Druh dokumentu: | article |
| ISSN: | 2055-2076 20552076 |
| DOI: | 10.1177/20552076221085061 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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