Details

Subject(s)

• COVID-19 Pandemic, 2020- [Browse]

Series

Policy research working papers. [More in this series]

Summary note

This study investigates whether Twitter data can be used to infer attitudes towards COVID-19 vaccination with an application to the Arabic speaking world. At first glance, anti-vaccine sentiment estimated from Twitter data is surprisingly low in comparison to estimates obtained from survey data. Only about 3 percent of Twitter accounts in our database are identified as anti-COVID-vaccination (compared to 20 to 30 percent of survey respondents). This bias is resolved when: (1) filtering out accounts belonging to organizations that make up a significant share of the discourse on Twitter, and (2) adjusting for the fact that the population of Twitter users is biased towards more educated individuals. The most effective messages on the anti-vaccine side highlight claims that the vaccine causes serious life-threatening side effects. In the pro-vaccine camp, tweets containing content showing public figures receiving the vaccine are found to have the largest reach by far.

Source of description

Description based on publisher supplied metadata and other sources.

Other title(s)

Inferring COVID-19 Vaccine Attitudes from Twitter Data

Other standard number

• 10.1596/1813-9450-10165

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