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

• Main Authors: Jianhong Jiang (Author), Chenyan Yao (Author), Xinyi Song (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2024.1320146
• Keywords: COVID-19; help-seeking behavior; social media; data mining; neural networks; regression analysis; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 12 (2024)

ObjectiveDuring the COVID-19 pandemic, people posted help-seeking messages on Weibo, a mainstream social media in China, to solve practical problems. As viruses, policies, and perceptions have all changed, help-seeking behavior on Weibo has been shown to evolve in this paper.MethodsWe compare and analyze the help-seeking messages from three dimensions: content categories, time distribution, and retweeting influencing factors. First, we crawled the help-seeking messages from Weibo, and successively used CNN and xlm-roberta-large models for text classification to analyze the changes of help-seeking messages in different stages from the content categories dimension. Subsequently, we studied the time distribution of help-seeking messages and calculated the time lag using TLCC algorithm. Finally, we analyze the changes of the retweeting influencing factors of help-seeking messages in different stages by negative binomial regression.Results(1) Help-seekers in different periods have different emphasis on content. (2) There is a significant correlation between new daily help-seeking messages and new confirmed cases in the middle stage (1/1/2022-5/20/2022), with a 16-day time lag, but there is no correlation in the latter stage (12/10/2022-2/25/2023). (3) In all the periods, pictures or videos, and the length of the text have a significant positive effect on the number of retweets of help-seeking messages, but other factors do not have exactly the same effect on the retweeting volume.ConclusionThis paper demonstrates the evolution of help-seeking messages during different stages of the COVID-19 pandemic in three dimensions: content categories, time distribution, and retweeting influencing factors, which are worthy of reference for decision-makers and help-seekers, as well as provide thinking for subsequent studies.