A Review of Sentimental Analysis for Vaccine Dataset Using BI-LSTM Method DOI

Alok Soreng,

Safdar Sardar Khan, Arpit Deo

и другие.

Опубликована: Дек. 8, 2023

In the age of digital communication, realm public opinion, particularly on pressing issues like vaccination, has found its voice through myriad online platforms. Given surge discussions around vaccines, especially in wake COVID-19 pandemic, there is an imperative need to decipher underlying sentiments from these vast datasets. Sentiment analysis, a prominent branch Natural Language Processing (NLP), provides tools extract, process, and categorize such sentiments. While traditional machine learning models have held their ground sentiment analysis tasks, intricate nature human emotions language patterns demands more refined techniques. The Bidirectional Long Short-Term Memory (BI-LSTM) model, enhanced variant recurrent neural networks, emerges as promising candidate with capability capture contextual information both past future data points sequences. This review paper delves into application efficacy BI-LSTM method for vaccine-related Through comprehensive we evaluate performance metrics, benefits, limitations, positioning against other prevalent models. findings suggest that holds significant potential providing nuanced insights regarding which instrumental stakeholders craft informed strategies communications.

Язык: Английский

A Review of Sentimental Analysis for Vaccine Dataset Using BI-LSTM Method DOI

Alok Soreng,

Safdar Sardar Khan, Arpit Deo

и другие.

Опубликована: Дек. 8, 2023

In the age of digital communication, realm public opinion, particularly on pressing issues like vaccination, has found its voice through myriad online platforms. Given surge discussions around vaccines, especially in wake COVID-19 pandemic, there is an imperative need to decipher underlying sentiments from these vast datasets. Sentiment analysis, a prominent branch Natural Language Processing (NLP), provides tools extract, process, and categorize such sentiments. While traditional machine learning models have held their ground sentiment analysis tasks, intricate nature human emotions language patterns demands more refined techniques. The Bidirectional Long Short-Term Memory (BI-LSTM) model, enhanced variant recurrent neural networks, emerges as promising candidate with capability capture contextual information both past future data points sequences. This review paper delves into application efficacy BI-LSTM method for vaccine-related Through comprehensive we evaluate performance metrics, benefits, limitations, positioning against other prevalent models. findings suggest that holds significant potential providing nuanced insights regarding which instrumental stakeholders craft informed strategies communications.

Язык: Английский

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