Can social media data be used to evaluate the risk of human interactions during the COVID-19 pandemic?

ABSTRACT: The U.S. has taken multiple measures to contain the spread of COVID-19, including the implementation of lockdown orders and social distancing practices. Evaluating social distancing is critical since it reflects the risk of close human interactions. While questionnaire surveys or mobility data-based systems have provided valuable insights, social media data can contribute as an additional instrument to help monitor the risk of human interactions during the pandemic. For this reason, this study introduced a social media-based approach that quantifies the pro/anti-lockdown ratio as an indicator of the risk of human interactions. With the aid of natural language processing and machine learning techniques, this study classified the lockdown-related tweets and quantified the pro/anti-lockdown r

SUBMITTER: Li L 

PROVIDER: S-EPMC7902209 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature