This thesis analyses German government communication on Twitter during the COVID-19 pandemic. Specifically, the influence of the government on economic policy topics is studied. By applying techniques of deep learning and concepts of natural language processing, the topics were extracted from the COVID-19 Twitter dataset collected from January 2020 to August 2020. The communication structures within the topics were investigated through social network analysis and the influence of the government in the network was identified. As a result, government communication was found to be widely spread across the themes. The examination of the economic policy communication networks showed a low influence on government communication. The analysis showed gaps in government communication especially in topics where restrictions on economic freedom of action were discussed.
You can find the thesis here: https://github.com/p-dre/Masterthesis/blob/main/Masterarbeit.pdf