1. How do German politicians interact on Twitter regarding COVID-19?

   - How often do they tweet? Are they just posting statuses or are they participating in discussions?

   - What is the sentiment expressed in their tweets?

   - What accounts (media, medical professionals) do they retweet?

2. How can the politicians be grouped according to the metrics from RQ1?

   - How do these groups relate to existing political groups (parties, factions)?

3. How do the forms of interaction change over time / course of the pandemic?

   - When did certain politicians start to talk about COVID-19?

   - How did their followers change over time?

   - Did their opinions on COVID-19 and political decisions regarding it change over time?

Answering these questions will help the general public get better insights into how politicians voice their opinions when dealing with a topic such as COVID-19. This will hopefully help people make more informed decisions when choosing how to participate in public debates, and build a clearer opinion on who they would like to vote for in upcoming elections. This project could also be of interest to data scientist who would like to work with the dataset we will be creating. Lastly, it could also be of interest to the politicians we choose to analyse, as it could help the reflect on how they present themselves online and in public.

Several methods are combined for the analysis:

• Natural Language Processing (e.g. Sentiment Analysis): Sentiment Analysis can be used to capture the sentiment of the tweets related to Covid-19.
• Social Network Analysis: This method can be used to map the relationship patterns of the respective politicians and identify groups.
• Interview: The results of the analysis can be verified and deepened through interviews with the respective politicians.

First we start with a literature research to our topic and defined it more precisely. Then we define the selection criteria for the politicians as well as for the needed tweets. Followed by the script writing for the data collection and the evaluation of them. This results get verified subsequently while on the side we write the paper. The peer-reviews start in mid-february. After that, we plan to have 4 weeks for the paper revision, preparing the video and the presentation.

Extract of the time schedule created with Agantty: