Emotions play a vital role in the behaviour of individuals during pandemics. Fear, for instance, increases the likelihood that citizens follow public health advice while hope can induce false optimism which can lead to lower levels of protective behavior. However, do political parties make strategic use of emotional appeals during pandemics? Furthermore, do these strategies succeed in actually influencing public opinion and thereby potentially citizens’ behaviour? To answer these questions, I use word embeddings and neural network classifiers to analyze social media output of political parties and different samples of the public in Germany during the first wave of the pandemic. Vector autoregression analyses (VAR) of time series show that the number of new COVID-19 cases per day predicts specific emotional rhetoric. While government parties increase fear and decrease hope, populist parties show the opposite strategy indicating a strategy of downplaying the crisis. Furthermore, comparing retweet volumes of political messages to emotional expressions in almost 200,000 public tweets suggests that populist radical right parties, rather than government parties, succeed in influencing public opinion, even beyond partisan lines. This finding can carry important implications for the level of protective behavior among the population.