In order to achieve these goals, we use a mixed methods design including discourse analysis of speeches, survey data, and computational methods. Through the latter the project will explore the opportunities for understanding online discourse on Twitter and provide a large scale corpus of COVID-19 related tweets. Our findings will be equally relevant for research and policy.

First we analyse the discourse through twitter communications of politicians and social stakeholders. Then we use those results to connect them to the individual level model. We then develop the theoretical background for how and why individuals develop solidary attitudes or engage in solidary behaviour in this context. The theoretical model will be empirically analysed - utilizing social science statistical modelling techniques - to identify the causal pathways in attitudinal changes and behavioural adaptations.

Two levels of analysis are applied:

  1. Individual citizens: We are interested in explaining solidarity in attitudes and behaviour of individuals
  2. Political elites and societal stakeholders: We will analyse the discourse on mitigation measures and its connection to solidarity frames.

Finally we allow the two levels of analysis, individuals and political elites and stakeholders, to interact, so that we can identify how elite discourse influences individual citizens.