Due to complicated regulations, the exact number of mandates in the German parliament is impossible to predict. While the coalition talks were still ongoing and it was unclear which parties would form the government, we already published an interactive with all MPs and details about them. The added value of this interactive is created by comparing population statistics with the politicians: Does the number of women, academics, people from Eastern Germany, the countryside or with immigration history represent German society? How does the income of an MP compare with average citizens?
Our election coverage was the backbone of 18 different newspapers’ reporting (all part of Funke media group). This project presenting the new MPs and allowing to compare the parliament’s formation with Germany’s population was the only one to present it with comparison figures for different professions, academic degrees, income, gender, migration background and age while other outlets sticked to presenting the composition of the new parliament or comparing it only with previous MPs in Germany’s history. Users spent a remarkable more than 6 minutes on the page on average to explore the details in depth.
The project is based on a state-of-the-art frontend technology stack using React with next.js, emotion for CSS-in-js, and d3 for data visualization. Some graphics were created manually with Adobe Suite’s Illustrator and embedded as svg’s. As most of our users visited the page on their smartphones, we paid extra attention to a good user experience on small devices with low bandwidth. Additionally, we split parts of the story into smaller pieces that could be embedded on other sites using iframes.
The dataset on MPs was created by a variety of sources using R: the official data published by the Federal Election office was matched with a larger database of all candidates that we had created prior to the elections, allowing us to research and categorize professions and additional data accordingly. Some data (e.g. on migration background) was collected from third parties and matched manually, as well.
What was the hardest part of this project?
One overall challenge with this project was the tight turnaround, as the interest in the new parliament peaks shortly after the results are published, but this coincides with the publication of all election results and with a team of merely 4 people responsible for more than 8 individual election dashboards with multiple modules each, capacities were limited and called for a smart preparation. The set-up of the project was therefore installed weeks before the elections already, and this is when we created a database of MP candidates and sorted them by likelihood of being elected in order to prioritize which details to manually research.
We created a script that took the free-text input from people’s candidacy files and grouped them into consistent professions. In the case of previous MPs we manually researched their professional background from before they entered parliamentary politics in order to represent different educational backgrounds and trends. We also created databases of census data, disaggregated by age, gender and federal state so users could compare the representation of a specific demographic among the MPs to the size of that same group in the general population.
A lot of work went into the behind-the-scenes of this application, which presents the parliament with a new twist – based on the democratic root concept of “representing the people”.
What can others learn from this project?
This project shows that it is worthwhile to supplement and expand official election data with your own research. We were able to add value and information by doing the cumbersome labor of manually collecting figures and data for comparison or processing the published data further. The resulting visualizations were a very intuitive and easy-to-understand format. The combination of an interactive that allows for user exploration as well as a linear story picking out and presenting the most interesting findings caters to different kinds of users preferences at the same time. Most importantly, the project focussed on one of the main questions of electoral politics that – due to a lack of easily accessible data – is seldomly centered in post-election coverage: how the voting population is represented, not only in terms of political affiliation but also based on other demographics and collective experiences.