Advancements in deep learning and natural language processing for effective disaster sentiment analysis: A review DOI Creative Commons
Yinghao Xu

Applied and Computational Engineering, Journal Year: 2024, Volume and Issue: 86(1), P. 284 - 293

Published: Aug. 14, 2024

This article comprehensively studies the application of deep learning (DL), natural language processing (NLP), and large models (LLM) in sentiment analysis disaster scenarios such as earthquakes major accidents. The focuses on latest developments these technologies their role strengthening management response. explores various methods, including BERT, LSTM, convolutional neural networks, with a focus practicality, challenges, potential for development. review aims to provide researchers relevant practitioners comprehensive understanding this rapidly developing field.

Language: Английский

Advancements in deep learning and natural language processing for effective disaster sentiment analysis: A review DOI Creative Commons
Yinghao Xu

Applied and Computational Engineering, Journal Year: 2024, Volume and Issue: 86(1), P. 284 - 293

Published: Aug. 14, 2024

This article comprehensively studies the application of deep learning (DL), natural language processing (NLP), and large models (LLM) in sentiment analysis disaster scenarios such as earthquakes major accidents. The focuses on latest developments these technologies their role strengthening management response. explores various methods, including BERT, LSTM, convolutional neural networks, with a focus practicality, challenges, potential for development. review aims to provide researchers relevant practitioners comprehensive understanding this rapidly developing field.

Language: Английский

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