Weibo public opinion analysis of emergencies using lexicon-based and deep learning approaches: a case study of the 12.18 Jishishan Seismic Event
Seismic events, as sudden natural disasters, significantly impact society and the economy. Analyzing post-disaster online public opinion helps quickly assess the situation, severity, and public needs, aiding sentiment management and emergency response. This study collected Sina Weibo public opinion...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
|
| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2025.2506470 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Seismic events, as sudden natural disasters, significantly impact society and the economy. Analyzing post-disaster online public opinion helps quickly assess the situation, severity, and public needs, aiding sentiment management and emergency response. This study collected Sina Weibo public opinion data within 24 h after the Ms6.2 earthquake that struck Jishishan County, Gansu Province, on December 18, 2023. The distribution characteristics of public opinion and micro-charity and the correlation between public attention and micro-charity participation were analyzed. Sentiment analysis was further conducted using an improved sentiment lexicon-based approach and the Text-CNN method. The results indicate that the public reactions were most intense within the first hour after the earthquake, followed by three subsequent fluctuations. In terms of sentiment, positive-sentiment blog posts were the most common. Regarding micro-charity, users in regions highly concerned about the ‘#Gansu Earthquake’ topic were more involved. Different from previous studies, this study reveals a positive correlation between media exposure and micro-charity, suggesting that provinces with greater emergency attention are more active in micro-charity. The findings of this study are significant for disaster emergency management and online public opinion analysis in the new era. |
|---|---|
| ISSN: | 1947-5705 1947-5713 |