This article was published in P24 (Platform for Independent Journalism) on November 16.
In my previous post, I've tried to explain why the image of Turkey's parliamentary election was wrong. The election map that circulates around all Turkish print and online media has a fallacy; millions are misrepresented.
After the parliamentary elections on June, the ruling Justice and Development Party (AKP) was not able to get the majority of the votes. That's why Turkey was pushed into dozens of coalition talks that never succeeded. Political parties tried every possible combination among Justice and Development Party, The Republican People's Party (CHP), the Nationalist Movement Party (MHP) and the Peoples' Democratic Party (HDP). These talks failed to result in a coalition. Nevertheless, people (especially the supporters of CHP and MHP) had a high hope for a change in the political scene.
Meanwhile, Efe Kerem Sözeri pondered on the mapping methodology of the elections. In his article, he said that "We need to look at the maps in a more colorful way for a fairer representation." The problem of these maps begins with the choice of 'the parameter to color the cities'. The map you see above, colors a city according to vote percentages. Let's have Artvin as an example. The city is painted into color orange in the main map, just because AKP got the 45% of the votes, where, on the other hand, CHP had 35%. But considering that both parties, in Artvin, have the same amount of deputies the importance of the vote percentage becomes insignificant. That's why Efe Kerem Sözeri, developed a methodology for a better representation of the election results. Getting inspired by his initiation I developed a different methodology to form a colorful and an interactive map.
As the aim of this map is to be able to show the percentage of the deputies, first I calculated the percentages of the elected deputies for each city (see figure 1). For instance, Adana had selected 14 deputies from four parties in which, AKP had 6, CHP had 4, HDP had 1 and MHP had 3. So this means, deputies are distributed as 43%, 29%, 7%, and 21% respectively. With these percentages, I've created pie charts for every city.
In the second phase, I used Photoshop to create 81 cities within different layers (see figure 2). After finishing the map, I blended the related pie chart with the city layer to have a more accurate representation of the election results (figure 3). And this part is the biggest flaw of the map. Although I have matched the centres of the cities and pie charts they do not represent the distribution of deputies precisely. This is mainly caused by two things. Firstly, it is the shape of the cities. And, secondly, my choice of using pie charts instead of generated squares (as in Sözeri's methodology).
After finishing the colored map in Photoshop, I used it as a background image for an interactive map in Tableau Public (figure 4). I already had created a pie chart-map for this election before. So, I had to combine these two maps. In order to do so, I adjusted the longitude and latitude of the background image (map) to fit the new, interactive map (figure5).
This is how I combined two methods to create a more accurate and fair map for Turkey's parliamentary election 2015. Although, the map has some flaws and for sure it is less aesthetic, this way of mapping can start a new way of thinking in data journalism.
Note for the map user: The map below is interactive. This means you can hover your mouse on the map to see the distribution of deputies in each city. You can filter the map to see the deputy distribution that belongs to the parties. You can do this simply by clicking the box next to the party name (AKP, CHP, HDP and MHP). You can also zoom in and out. You can click the 'house' button to reset the map.
A second note for the map user: The numner of elected MPs differ from one source to another. In Şanlıurfa, for example, according to Hürriyet, 8 AKP MPs are elected, where on the other hand it is 9 in Habertürk's data.
An Alternative Map for Turkey's Parliamentary Elections 2015
As I mentioned before I had created a pie-chart map before combining two different methods to create the election map. So here is the additional map;