A multidimensional comparative study of help-seeking messages on Weibo under different stages of Covid-19 pandemic in China
Bibliographic Data
| ID | 22088366 |
|---|---|
| Authors | Jianhong Jiang, Jian‐Hong Jiang (0000-0001-6675-1964, Guilin University of Electronic Technology), Chenyan Yao (Guilin University of Electronic Technology, corresponding author), Xinyi Song (0000-0003-1741-4747, Guilin University of Electronic Technology) |
| Year | 2024 |
| Volume | 12 |
| Pages | 1320146-1320146 |
| Publication date | 2024-02-14 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2024.1320146 |
| PMID | 38420033 |
| OpenAlex | W4391815726 |
| Language | EN |
| References cited | 53 |
Objective: During 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. Methods: We 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. Conclusion: This 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
2019-20 coronavirus outbreak · Betacoronavirus · China · Disease · Geography · Outbreak · Pandemic · Pathology · Computer Science · Digital Marketing and Social Media · Medicine · Misinformation and Its Impacts · Sentiment Analysis and Opinion Mining · Virology
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Breadth, depth, and speed
| Citation velocity | historical |
|---|---|
| Highly cited | No |