Exposure to misinformation: Patterns and predictors

Using web survey data in the four studied cities, this chapter explores the patterns of exposure to debunked yet popularly circulated COVID-19 misinformation on social media such as WeChat, Facebook, and Twitter. It examines the types of COVID-19 misinformation (e.g., infectiousness, transmission routes, protection measures, and vaccines) that the respondents encounter the most often, and ties the encounters to their demographic characteristics and social differentiators. It further analyzes individual-level predictors and societal-level factors that affect respondents’ exposure to COVID-19 misinformation, including comparisons of the similarities and differences of exposure to COVID-19 misinformation across the four cities studied. The insight from the key findings is that full access to digital media and transparency reduce exposure to misinformation.