Disaster Related Tweets Analysis with Machine Learning Approaches-Reference-Cited by-同舟云学术

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Disaster Related Tweets Analysis with Machine Learning Approaches

Published:2023-11-24 Issue: Volume:4 Page:1-7
ISSN:
Container-title:2023 2nd International Conference on Futuristic Technologies (INCOFT)
language:
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Author:

Islam Taminul¹,Islam Monjurul²,Rudra Rahul³,Pranto Ismail Hossain⁴,Mahmud Md.Tanvir¹,Rahman Foysal Md. Musfiqur¹

Affiliation:

1. Daffodil International University,Department of Computer Science and Engineering,Dhaka,Bangladesh

2. JAIN(Deemed-to-be University),Department of Civil Engineering,Bengaluru,India

3. Maulana Abul Kalam Azad University of Technology,Department of Computer Science and Engineering,Kolkata,India

4. American International University-Bangladesh,Department of Computer Science and Engineering,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424959/10424987/10425631.pdf?arnumber=10425631

Reference35 articles.

1. Comparing Learning-Based Methods for Identifying Disaster-Related Tweets

2. Relevancy assessment of tweets using supervised learning techniques: Mining emergency related tweets for automated relevancy classification;Habdank,(2018)

3. Structural Stability in Physics

4. Voices in the Storm: The Lost Discourse of Climate Change in Hurricanes Harvey and Irma

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