Social media-based COVID-19 sentiment classification model using Bi-LSTM

作者：

Highlights：

• Bi-LSTM sentiment detection model is developed to classify COVID-19 social comments.

• Various scenarios to help counter negative COVID-19 comments and reduce their impact.

• Comparative analysis of our approach with most popular models is presented.

• Word embedding followed by Bi-LSTM provides better performance on Sentiment Analysis.

摘要

•Bi-LSTM sentiment detection model is developed to classify COVID-19 social comments.•Various scenarios to help counter negative COVID-19 comments and reduce their impact.•Comparative analysis of our approach with most popular models is presented.•Word embedding followed by Bi-LSTM provides better performance on Sentiment Analysis.

论文关键词：Bi-LSTM,COVID-19,Deep learning,Natural language processing,Sentiment classification,Social media

论文评审过程：Received 7 November 2021, Revised 26 June 2022, Accepted 25 August 2022, Available online 30 August 2022, Version of Record 7 September 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118710