Tracking social media during the COVID-19 pandemic: The case study of lockdown in New York State

作者：

Highlights：

• Analysis of social network data to detect and monitor public attitude towards intervention measures during a pandemic.

• Data distillation approach adapted for training data augmentation using only a small set of manually-labeled tweets.

• A Twitter-based case study of public opinion on lockdown policy in New York State during COVID-19 pandemic.

• Released a new annotated dataset of COVID-19-related tweets.

摘要

•Analysis of social network data to detect and monitor public attitude towards intervention measures during a pandemic.•Data distillation approach adapted for training data augmentation using only a small set of manually-labeled tweets.•A Twitter-based case study of public opinion on lockdown policy in New York State during COVID-19 pandemic.•Released a new annotated dataset of COVID-19-related tweets.

论文关键词：Stance detection,Opinion monitoring,Social media,Data distillation,Government policy

论文评审过程：Received 14 April 2021, Revised 18 August 2021, Accepted 22 August 2021, Available online 11 September 2021, Version of Record 21 September 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115797