"Help Us!": a content analysis of COVID-19 help-seeking posts on Weibo during the first lockdown

Abstract

Background: Social media is playing an increasingly important role in public emergencies for help-seekers, especially during the global COVID-19 pandemic. Wuhan, China, firstly official reported COVID-19 cases and implemented lockdown measures to prevent the spread of the virus. People during the first lockdown were restricted from seeking help face-to-face. Social media is more prominent as an online tool for people seeking help, especially for patients, than in other stages of the COVID-19 pandemic.

Objective: This study aimed to explore the urgent needs presented in help-seeking posts in Wuhan during the first COVID-19 lockdown, the content features of these posts, and how they influenced online user engagement.

Methods: This study collected posts from Weibo posted with specific help tags during the first COVID-19 lockdown in Wuhan: from 23 January 2020 to 24 March 2020, and eventually received 2055 data, including textual content, comments, retweets, and publishing location. Content analysis was conducted, and manual coding was performed on help-seeking typology, narrative mode, narrative subject, and emotional valence.

Results: The result showed that help-seeking posts primarily were seeking medical (97.7%). Features of these posts were mainly adopting a mixed narrative mode (46.4%), released by relatives of patients (61.7%), and expressing negative emotions (93.2%). Chi-square tests suggested that help-seeking posts with mixed narrative modes released by relatives express more frequent negative emotions. Results of negative binomial regression indicated posts of seeking information (B = 0.52, p < .001, e^0.52 = 1.68), with mixed narrative mode (B = 0.63, p < .001, e^0.63 = 1.86), released by themselves (as referential groups) and with neutral emotions increased comments. Posts of seeking medical (B = 0.57, p < .01, e^0.57 = 1.77), with mixed narrative mode (B = 1.88, p < .001, e^1.88 = 6.53), released by people of unrelated patients (B = 0.47, p < .001, e^0.47 = 1.60) and with neutral emotions increased retweets.

Conclusions: This study provides evidence of what actual public demands are to be considered and addressed by governments and public administrators before implementing closure and lockdown policies to limit the spread of the virus. Meanwhile, our findings offer strategies for people help-seeking on social media in similar public health emergencies.

Keywords: COVID-19; Lockdown; Online help-seeking; Public engagement; Social media.