• How do german institution and public spokespersons communicate during and about the coronavirus on Twitter?
• What is the behaviour of their followers and how do they relate in a Network?
• How do Replies and Quoted Retweets get used around this subject (i.e. to agree/disagree with original tweet?)
• How can debate structure in the replies be described?
• Which linguistic characteristics can be found and how different are they between the different accounts?

By finding answers to these questions we aim to offer a better overview on the debate structure around COVID-19 in Germany. By analyzing the replies to official institutions and well known public spokespersons we can gain an insight on public german opinion around the coronavirus and the measures taken to contain its spread.

Methods we currently plan on using:

• Natural language processing (i.e. sentiment analysis)
• Social network analysis (i.e. show relations between the different accounts and their followers)
• Some form of qualitative analysis
• Generation of a corpus of tweets

• Clarification of our research questions and some open questions (i.e. scrape tweets from now on or use historic tweets as well)
• Create a List of twitter accounts we want to use for our analysis.

• Scrape tweets to create our corpus.
• Carry out our qualitative analysis.
• Prepare code for our analysis.

• Carry out our analysis of the corpus (distant reading and social network analysis)

• Write our paper.
• Peer review other paper.