Mining Local Social Media Data for Public Information Work: Insights from the COVID-19 Pandemic

Abstract

During crisis events, social media have become important communication channels, but the sheer volume of public-generated data can challenge those managing public information. This paper explores how social media posts from individuals local to a crisis can provide valuable insights. Using a case study of Twitter activity from Colorado during the early stages of the COVID-19 pandemic, we categorize tweets into three main areas: reports on COVID-19, discussions on social distancing, and conversations about the broader effects of the pandemic. These tweets provided insight into how people were responding, including posts they found confusing, misinterpretations of data, and the spread of misinformation and false rumors. Results demonstrate the need for those responsible for public information work to engage with and respond to local perspectives and concerns in their messaging.