A Multidimensional Study of the 2023 Beijing Extreme Rainfall: Theme, Location, and Sentiment Based on Social Media Data
Extreme rainfall events are significant manifestations of climate change, causing substantial impacts on urban infrastructure and public life. This study takes the extreme rainfall event in Beijing in 2023 as the background and utilizes data from Sina Weibo. Based on large language models and prompt...
Saved in:
| Main Authors: | Xun Zhang, Xin Zhang, Yingchun Zhang, Ying Liu, Rui Zhou, Abdureyim Raxidin, Min Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/14/4/136 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
On the emergence of rainfall extremes from ordinary events
by: E. Zorzetto, et al.
Published: (2016-08-01) -
Evaluating COVID-19 public discourse for sentiment, topic, and geolocation analysis
by: Festus A. Omojowo, et al.
Published: (2025-05-01) -
Reddit comment analysis: sentiment prediction and topic modeling using VADER and BERTopic
by: Denilson de Oliveira Silva, et al.
Published: (2024-12-01) -
Regional trending topics mining from real time Twitter data for sentiment, context, network and temporal analysis
by: Mousumi Hasan, et al.
Published: (2025-03-01) -
Stability analysis of geosynthetic-reinforced soil bridge abutments under extreme rainfall conditions
by: Qiangqiang HUANG, et al.
Published: (2025-04-01)