TweetACE: A Fine-grained Classification of Disaster Tweets using Transformer Model
Author:
Affiliation:
1. Missouri University of Science and Technology,Computer Science,Rolla,United States
2. Meharry Medical College,School of Applied Computational Sciences,Nashville,United States
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10440654/10440655/10440656.pdf?arnumber=10440656
Reference23 articles.
1. HatEmoTweet: low-level emotion classifications and spatiotemporal trends of hate and offensive COVID-19 tweets
2. IDRISI-RE: A generalizable dataset with benchmarks for location mention recognition on disaster tweets
3. Covid-19 Control: Face Mask Detection Using Deep Learning for Balanced and Unbalanced Dataset
4. Target oriented tweets monitoring system during natural disasters
5. Incident Tweets;Schulz,2016
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. CURD: Context-aware Relevance and Urgency Determination;Proceedings of the 36th International Conference on Scientific and Statistical Database Management;2024-07-10
2. A Novel Approach to Handle Disaster with Twitter Reports by Deep Learning;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17
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