Polarization of Opinions on COVID-19 Measures: Integrating Twitter and Survey Data

Abstract

Polarization of public opinion is a major issue for societies, as high levels can promote adverse effects such as hostility. The present paper focuses on the polarization of opinions regarding COVID-19 prevention measures in survey data and on Twitter in the German-speaking regions of Germany, Austria, and Switzerland. The level of polarization is measured by dispersion and bimodality in the opinions based on the sentiment in Twitter data and the agreement in the survey data. Our paper, however, goes beyond existing research as we consider data from both sources separately and comparatively. For this purpose, we matched individuals’ survey responses and tweets for those respondents who shared their Twitter account information. The analyses show that vaccination is more polarizing compared to mask wearing and contact tracing in both sources, that polarization of opinions is more pronounced in the survey data compared to the Twitter data, but also that individuals’ opinions about the COVID-19 measures are consistent in both sources. We believe our findings will provide valuable insights for integrating survey data and Twitter data to investigate opinion polarization.