Harvesting Natural Disaster Reports from Social Media with 1D Convolutional Neural Network and Long Short-Term Memory-Reference-Cited by-同舟云学术

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Harvesting Natural Disaster Reports from Social Media with 1D Convolutional Neural Network and Long Short-Term Memory

Published:2023-12-08 Issue: Volume:10 Page:1-6
ISSN:
Container-title:2023 Eighth International Conference on Informatics and Computing (ICIC)
language:
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Author:

Budiman Irwan¹,Faisal Mohammad Reza¹,Nugrahadi Dodon Turianto¹,Muliadi ¹,Delimayanti Mera Kartika²,Prastya Septyan Eka³

Affiliation:

1. Lambung Mangkurat University,Department of Computer Science,Banjarbaru,Indonesia

2. Politeknik Negeri Jakarta,Computer and Informatics Engineering Department,Depok,Indonesia

3. Sari Mulia University,Department of Information Technology,Banjarmasin,Indonesia

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10381889/10381891/10382045.pdf?arnumber=10382045

Reference22 articles.

1. Analysis of New Features on the Performance of the Support Vector Machine Algorithm in Classification of Natural Disaster Messages

2. The Effect of Pre-Processing on the Classification of Twitter’s Flood Disaster Messages Using Support Vector Machine Algorithm

3. Natural Disaster on Twitter: Role of Feature Extraction Method of Word2Vec and Lexicon Based for Determining Direct Eyewitness

4. Automatic identification of eyewitness messages on twitter during disasters

5. Applying Features Based on Word Embedding Techniques to 1D CNN for Natural Disaster Messages Classification

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