Two clustering methods to determine users with similar opinions on the Covid-19 pandemic and the related public debate in Germany will be presented in this paper. We believe, they can help gaining an overview over similar-minded groups and could support the prevention of fake-news distribution. The first method uses a new approach to create a network based on retweet- relationships between users and the most retweeted users, the so-called influencers. The second method extracts hashtags from users posts to create a “user feature vector” which is then clus-tered, using a consensus matrix based on previous work, to identify groups using the same lan-guage. With both approaches it was possible to identify clusters that seem to fit groups of differ-ent public opinions in Germany. However, we also found that clusters from one approach can-not be associated with clusters from the other due to filtering steps in the two methods.