Polarisation and Silencing Others During the COVID-19 Pandemic in Germany: An Experimental Study Using Algorithmically Curated Online Environments

In 2020, societies debated the use of government restrictions on public life to stem the COVID-19 pandemic. Many of these debates took place online. The Internet enables people to come into contact with like-minded content. Algorithms based on collaborative filtering can contribute to this process and might lead to homogenous like-minded online environments that contribute to a polarisation of society. This article therefore examines the effects of (1) like-minded versus opposing online environments, which were (2) randomly versus algorithmically curated. Data from a between-subject experiment embedded in a two-wave panel survey of German citizens (n = 318) show that attitude polarisation as well as affective polarisation are largely independent of exposure to different online environments. Moreover, the results indicate that polarised attitudes of supporters and opponents of the COVID-19-related restrictions relate to varying degrees of beliefs in the importance of silencing people with opposing opinions: While supporters’ polarised attitudes are positively related to the belief in the importance of silencing others, opponents’ polarised attitudes are rather negatively related to such beliefs.