This visualization lets the reader explore the complex process of forming a government in Finland. In a gamelike fashion you can try different coalitions and see if the parties you have chosen agree or disagree and if you can succeed to get a majority of the MPs to support you politics. The data used was th eelection reults in the 2019 Finnish Parliamentary election, the individual MPs answers to Yles election compass as well as the parties answers to the election compass.
The visualisation was well recieved and reposted every time there was a new twist in the forming of the government and later in the fall when there was a governmet crisis. It has been used in schools as a part of social studies education to show how a finnish government is formed.
The government game was one of the finalists in the application category at the NODA awards 2019 (Best Nordic datajournalism) and regarded to be the best application that shows how you form a government that the jury had seen.
The visualization was also translated in to finnish an published at Yle.fi and widely discussed among finnish political commentators.
We had analysed the candidates answers in Yles election compass for anouther piece ealrier and done a political compass (https://svenska.yle.fi/artikel/2019/04/04/centern-mer-vanster-an-sdp-se-var-partierna-finns-pa-den-politiska-kompassen) using R and psych. The visualization is built using Vue JS. The visualizastion calculates the parties mandate, where the MPs and the parties positioned themselves on the political compass, how many questions the parties agreed on and which questions that seperated them.
The storytelling goes from basic to more in depth information the further you read.
What was the hardest part of this project?
We tried many different ways to visualize how to form a majority government. The level of nerdieness in the texts was also challenging. You need to be correct but still readable. We are happy that as young students 12-year olds have been able to understand it.
What data to show as a visual elemant and what to generate as text was also a issue we discussed a lot.
The visualisation was published just two days after the election so much of the preparation was made beforehand. We published five different datastories about the election results (maps, demographic datastory, the new MPs on the political compass etc) so effective time management was wery important for this to be possible.
What can others learn from this project?
It is easy to outsmart the audience when it comes to topics that you are very familiar with. Not every one knows that much about politics as you would think. The biggest lesson from this was that it pays of to be as clear an understandable as you possilbly can even tough it is much harder to explain things that way.