A computational analysis of German online discourses about COVID-19 vaccinations to inform policy-making in times of crisis (Preprint)

BACKGROUND Societies worldwide have witnessed growing rifts separating advocates and opponents of vaccinations and other COVID-19 countermeasures. With the rollout of vaccination campaigns, the German-speaking DACH region (Germany, Austria, Switzerland), initially exhibited a noticeably low vaccination uptake compared to other European regions. Later, uptake increased. It remains unclear which factors contributed to these changes. OBJECTIVE This study aims to shed light on the intricacies of vaccine hesitancy among the German-speaking population and the possible dynamics between policy changes and public concerns using online discourse data. These insights are valuable for policy-makers tasked with making far-reaching decisions: policies need to effectively curb the spread of the virus and at the same time respect fundamental civic liberties and minimize undesired consequences. METHODS This study draws on data from X , formerly Twitter. We use a hybrid pipeline to detect and analyze 191,750 German vaccination-related tweets using a semi-automatic seed list generation approach, topic modeling, sentiment analysis, and a minimum of social scientific domain knowledge to analyze the discourse about vaccinations in the light of the COVID-19 pandemic. We further analyze the evolution of public attention during different phases of the pandemic and in relation to policy changes to identify potential drivers of shifts in public attention. RESULTS We find that skepticism regarding the severity of the COVID-19 virus, towards efficacy and safety of vaccines and other medical concerns were among the prevalent topics in the discourse on Twitter but that the most attention was given to debating the theme of freedom and civic liberties. During the later phases of the pandemic, policies were implemented that restricted the freedom of unvaccinated citizens. During these phases, increased vaccination uptake could be observed, and the attention increasingly shifted from medical and other concerns towards questions of freedom and civic liberties. Yet, increasingly negative and polarized sentiments were expressed. CONCLUSIONS Our analyses suggest potential interactions between policies, public attention to different topics and associated sentiments. While vaccination uptake increased, our findings indicate that citizens' doubts and concerns did not decrease. This study showcases the use of analyzing online discourse data for data-driven policy-making in highly dynamic contexts such as the COVID-19 pandemic where monitoring the discourse can serve to provide insights on suitable actions to properly and timely respond to citizens' concerns.