Unveiling the dynamics of crisis events: Sentiment and emotion analysis via multi-task learning with attention mechanism and subject-based intent prediction
In the age of rapid internet expansion, social media platforms like Twitter have become crucial for sharing information, expressing emotions, and revealing intentions during crisis situations. They offer crisis responders a means to assess public sentiment, attitudes, intentions, and emotional shift...
Saved in:
Main Authors: | WIN MYINT, Phyo Yi, LO, Siaw Ling, ZHANG, Yuhao |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8696 https://ink.library.smu.edu.sg/context/sis_research/article/9699/viewcontent/DynamicsCrisisEvents_pvoa_cc_by_nc.pdf |
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) -
Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
by: Poria, S., et al.
Published: (2014) -
FROM SEMANTIC TO EMOTIONAL SPACE IN SENSE SENTIMENT ANALYSIS
by: MITRA MOHTARAMI
Published: (2013) -
Investigating the characteristics and research impact of sentiments in tweets with links to computer science research papers
by: Jothiramalingam, Keerthana, et al.
Published: (2019) -
How intense are you? Predicting intensities of emotions and sentiments using stacked ensemble [application notes]
by: Akhtar, M. S., et al.
Published: (2021)