Using Natural Language Processing and Computer Vision to Measure Global Impacts of Extreme Weather Hazards
Lead Research Organisation:
University of Exeter
Department Name: Computer Science
Abstract
Extreme weather causes major disruption and risk to life worldwide. This PhD will develop robust computational tools to systematically observe the social impacts of extreme weather based on social media and online news. This addresses an outstanding lack of social impact observations to validate forecasts and improve impact-based warning systems.
The research is split into three experimental questions, with the overarching objective to measure the social impacts of extreme weather hazards at global scale.
1) How can natural language processing (NLP) help characterise extreme weather event impacts using short-form social media text?
2) How can NLP monitor extreme weather events globally using long-form text from news articles?
3) Can computer vision determine hazard impacts from images and video?
The research is split into three experimental questions, with the overarching objective to measure the social impacts of extreme weather hazards at global scale.
1) How can natural language processing (NLP) help characterise extreme weather event impacts using short-form social media text?
2) How can NLP monitor extreme weather events globally using long-form text from news articles?
3) Can computer vision determine hazard impacts from images and video?
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513210/1 | 01/10/2018 | 30/09/2023 | |||
| 2578516 | Studentship | EP/R513210/1 | 01/10/2021 | 31/03/2025 | James Young |
| EP/T518049/1 | 01/10/2020 | 30/09/2025 | |||
| 2578516 | Studentship | EP/T518049/1 | 01/10/2021 | 31/03/2025 | James Young |