The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic

Chen, Ninghan; Chen, Xihui; Zhong, Zhiqiang; Pang, Jun

doi:10.1007/978-3-031-26390-3_15

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Measuring COVID-19 Vaccine Hesitancy: Consistency of Social Media with Surveys

Chen

Pang

et al. 2022

Lecture Notes in Computer Science

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We validate whether social media data can be used to complement social surveys to monitor the public's COVID-19 vaccine hesitancy. Taking advantage of recent artificial intelligence advances, we propose a framework to estimate individuals' vaccine hesitancy from their social media posts. With 745,661 vaccine-related tweets originating from three Western European countries, we compare vaccine hesitancy levels measured with our framework against that collected from multiple consecutive waves of surveys. We successfully validate that Twitter, one popular social media platform, can be used as a data source to calculate consistent public acceptance of COVID-19 vaccines with surveys at both country and region levels. In addition, this consistency persists over time although it varies among socio-demographic sub-populations. Our findings establish the power of social media in complementing social surveys to capture the continuously changing vaccine hesitancy in a global health crisis similar to the COVID-19 pandemic.

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