Empowering crisis information extraction through actionability event schemata and domain-adaptive pre-training
One of the persistent challenges in crisis detection is inferring actionable information to support emergency response. Existing methods focus on situational awareness but often lack actionable insights. This study proposes a holistic approach to implementing an actionability extraction system on so...
Saved in:
Main Authors: | ZHANG, Yuhao, LO, Siaw Ling, WIN MYINT, Phyo Yi |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/9721 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Transformer-based Multi-Task Learning for crisis actionability extraction
by: ZHANG, Yuhao, et al.
Published: (2023) -
Unveiling the dynamics of crisis events: Sentiment and emotion analysis via multi-task learning with attention mechanism and subject-based intent prediction
by: WIN MYINT, Phyo Yi, et al.
Published: (2024) -
Impact of difficult negatives on Twitter crisis detection
by: ZHANG, Yuhao, et al.
Published: (2023) -
Situational crisis communication and interactivity: Usage and effectiveness of Facebook for crisis management by Fortune 500 companies
by: Ki, E.-J., et al.
Published: (2016) -
REMEMBERING IN CRISIS COMMUNICATION: CRISIS MEMORY MAKING OF SARS ON CHINESE SOCIAL MEDIA DURING COVID-19
by: ZHANG XING
Published: (2023)