Social media data-based typhoon disaster assessment
Bibliographic Data
| ID | 22028320 |
|---|---|
| Authors | Zi Chen (0009-0001-1175-1470, UNSW Sydney, corresponding author), Samsung Lim (0000-0001-9838-8960, UNSW Sydney) |
| Year | 2021 |
| Volume | 64 |
| Pages | 102482 |
| Publication date | 2021-10-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2021.102482 |
| OpenAlex | W3185988473 |
| Language | EN |
| Citations received | 14 |
| References cited | 25 |
Data science · Geography · Natural language processing · Situation awareness · Situational ethics · Social media · Typhoon · World Wide Web · Computer Science · Disaster Management and Resilience · Engineering · Psychology · Public Relations and Crisis Communication · Seismology and Earthquake Studies · Artificial Intelligence
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Assessing disaster impacts and response using social media data in China
Leveraging multimodal social media data for rapid disaster damage assessment
Determining disaster severity through social media analysis
An emotional step toward automated trust detection in crisis social media
Tracking and Analyzing Public Emotion Evolutions During Covid-19
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
GeoWeb and crisis management
| Unique citing works | 14 |
|---|---|
| Citations per year | 4,67 |
| Citation span | 2023 - 2025 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 13 |