Insight into public sentiment and demand in China’s public health emergency response
A weibo data analysis
Bibliographic Data
| ID | 15365751 |
|---|---|
| Authors | Yanping Wang (0000-0002-2463-0555, Harbin Medical University, corresponding author), Min Wei (0000-0002-3131-0955, Harbin Medical University), Peng Wang (0000-0003-3639-6126, Harbin Medical University), Yiran Gao (0000-0003-0054-633X, Harbin Medical University), Yu Tian (0000-0002-2744-2226, Harbin Medical University), Tian Yu (0009-0006-1427-0740), Nan Meng (0000-0001-9371-160X, Harbin Medical University), Huan Liu (0000-0001-8772-1545, Harbin Medical University), Xin Zhang (0000-0003-0184-5868, Harbin Medical University), Kexin Wang (0009-0006-0995-438X), Qunhong Wu (0000-0002-2873-5266) |
| Year | 2025 |
| Volume | 25 |
| Issue | 1 |
| Pages | 1349-1349 |
| Publication date | 2025-04-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-025-22553-2 |
| PMID | 40211194 |
| OpenAlex | W4409318158 |
| Language | EN |
| References cited | 38 |
The study underscores the complexity of public sentiment during the epidemic, with significant concerns about material safety and information security management. Public demands span basic survival needs to higher-order concerns such as education and legal protections. The findings suggest that policy-making processes must become more responsive, transparent, and equitable, incorporating real-time public feedback and ensuring comprehensive policies and legal systems are in place to address multifaceted public demands effectively
Biostatistics · China · Emergency response · Environmental health · Medical emergency · Pathology · Public health · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Influenza Virus Research Studies · Medicine · Nursing · Epidemiology
Sentiment Analysis and Opinion Mining
Covid-19
Infodemiology and Infoveillance
The effect of travel restrictions on the spread of the 2019 novel coronavirus (Covid-19) outbreak
From the Highest Employment Growth to the Deepest Fall
Network Structure and Community Evolution Online
Understanding the evolutions of public responses using social media
Artificial intelligence vs Covid-19
Predicting Infectious Disease Using Deep Learning and Big Data
Does government social media promote users' information security behavior towards Covid-19 scams? Cultivation effects and protective motivations
| Citation velocity | historical |
|---|---|
| Highly cited | No |