Optimism and pessimism analysis using deep learning on COVID-19 related twitter conversations

作者：

Highlights：

• A new deep learning approach to understand how optimism and pessimism feelings are conveyed in COVID-19 twitter conversations.

• Two new annotated corpora to evaluate optimism and pessimism predictive models over social media posts.

• A transfer learning approach based on the BERT model for predicting optimism and pessimism in tweets.

• Provides a relevant tool for the management of pandemics, health crises and trauma-related stress.

摘要

•A new deep learning approach to understand how optimism and pessimism feelings are conveyed in COVID-19 twitter conversations.•Two new annotated corpora to evaluate optimism and pessimism predictive models over social media posts.•A transfer learning approach based on the BERT model for predicting optimism and pessimism in tweets.•Provides a relevant tool for the management of pandemics, health crises and trauma-related stress.

论文关键词：Covid-19 pandemic,Sociome,Conversation,Emotion classification,Emotion shift

论文评审过程：Received 24 June 2021, Revised 16 February 2022, Accepted 23 February 2022, Available online 25 February 2022, Version of Record 4 March 2022.

论文官网地址：https://doi.org/10.1016/j.ipm.2022.102918