Can people hear others’ crying?: A computational analysis of help-seeking on Weibo during COVID-19 outbreak in China

A multidimensional comparative study of help-seeking messages on Weibo under different stages of COVID-19 pandemic in China

“…When disaster strikes, it is wise to @ the more influential people. Numerous studies have demonstrated the positive effect of @ on information diffusion ( 21 , 48 , 49 ), and Zhou et al ( 3 ) also confirmed the positive effect of @ on the number of retweets in their study of help-seeking messages in the early stage of the COVID-19 pandemic.…”

“…According to Weibo’s Unaudited Financial Results for the Fourth Quarter and Fiscal Year 2022, published on March 1, 2023, there were 586 million monthly active Weibo users in December 2022, with a net increase of about 13 million users year-on-year. In addition, it has been demonstrated that the number of retweets of help-seeking messages on Weibo has a significant positive effect on whether help-seekers receive actual help, and the number of help-seeking messages has a positive effect on the prediction of new confirmed diagnoses ( 3 ). Therefore, the study of help-seeking messages on Weibo is of great theoretical and practical significance.…”

“…The speed refers to the efficiency of the information diffusion process. Scholars have researched the influencing factors of Weibo help-seeking messages on Weibo in the early pandemic from different aspects such as diffusion size ( 3 , 20 , 27 ) and diffusion depth ( 23 ). In terms of the selection of factors, researchers generally agree that content characteristics and posting user’s characteristics can significantly contribute to the diffusion of the message ( 21 , 39 , 40 ).…”

“…The location of the message is also important ( 42 ). Zhou et al ( 3 ) proposed the content-context-connection(3C) framework to explain the effect of message dissemination on social media, and the location of the message, such as posting in hypertext or posting in Hubei, is included in the “context.” Besides the three factors of content, user and posting location, this paper will innovatively examine the effect of how quickly a message is first reposted on the size of the diffusion ( Figure 2 ).…”

“…There is a relative abundance of research on the factors influencing the retweeting of help-seeking messages in the early period of the pandemic ( 3 , 20 , 23 , 27 ), but there is a lack of empirical studies on this issue for the middle and later stages of the pandemic. This paper complements existing research on the factors influencing the retweeting of help-seeking information in other periods by exploring stable factors that have an impact on retweets’ number in all periods, as well as unstable factors that only play a significant role in individual periods, so as to provide advice and assistance to help-seekers (RQ3).…”