[EDIT 5/2/2014 : The vote shares of towns/’ilce’s actually reflect the city-level municipality preference of the town occupants not the vote share for that town’s mayoral elections. Therefore, color of a town not necessarily represent the party of the mayor of the town]
I am writing this post as of April 22nd, after 23 days of 2014 local elections in Turkey. YSK, AA, CIHAN, AKP, MHP, neither made the ballot box data available to the public yet. Sandik Buglari (i.e. Ballot box bugs, in Turkish) shared it on their Facebook page. Here is the link to data in spreadsheet. The data source is compiled from STS-CHP online ballot box management system, probably by Eren Yanik.
I had created maps of ballot boxes in colored markers here and attempted creating heatmaps here, yet I had failed in effectively representing the vote share difference of parties in towns. For example, in many towns, AKP won with a slight margin while it did much better in some other towns. I wanted to reflect this on a map and achieved this by creating several intensity maps as discussed below.
Intensity Maps by Google Fusion Tables
How to create intensity maps with custom boundaries on Google Fusion Tables is explained here. Before attempting these mappings, I just wanted to play and experience with it while meeting some interests on the last elections. Among other maps, I first would like to present four color town (ilce) map of Turkey, because, to the best of my knowledge, there is no town map of the elections other than mine (although there are city maps out there):
Maps are interactive, you can click/tap on a town to get vote share distribution of the four parties in that particular town.
- AK Party: Yellow
- CHP: Red
- MHP: Blue
- BDP/HDP: Purple
I edited the KML shape file of 2009 local election map made available here by Google/CIHAN. Since that elections some new ilces have been formed and names of some have been changed. I should admit that matching new ilce names in CHP-STS dataset with the old Google table was a pretty difficult/cumbersome task for me, I had to read online newspapers to figure them out.
City: New town name > Old (2009) town name
Aydin: Efeler > Merkez
Balikesir: Karesi Ve Altieylul > Merkez
Denizli: Merkezefendi > Merkez ; Pamukkale > Akkoy
Hatay: Antakya Defne Arsuz Payas > Merkez
Kahramanmaras: Dulkadiroglu Onikisubat > Merkez
Manisa: Sehzadeler Yunusemre > Merkez
Malatya: (Battalgazi + Yesilyurt) / 2 > Merkez [district names not removed]
Mardin: Artuklu > Merkez
Mugla: Fethiye Seydikemer > Fethiye ; Mentese > Merkez
Siirt: Tillo > Aydinlar
Tekirdag: Ergene Kapakli Suleymanpasa > Merkez
Trabzon; Ortahisar > Merkez
Urfa: Eyyubiye Haliliye Karakopru > Merkez
Van: Ipekyolu Tusba > Merkez
Zonguldak: Merkez Kilimli Kozlu > Merkez
cagliyancerit > caglayancerit ; m.kemalpasa > mustafakemalpasa ; 19_mayis > ondokuzmayis ;
Ordu: Altinordu > Merkez
Single Party Intensity Maps
In the winning party map above, one cannot see how well non-winners did in that town. To solve this problem I created several kinds of maps. First, same color map distribution of all:
Second attempt, every party is a different color:
By having parties in different maps we have some difficulty of doing pairwise comparisons. So, I created three maps to ease pairwise comparing.
As Interactive Google Maps with legends (light/dark colors denote the difference of the vote shares of the two, not the actual winning party):
- AKP-BDP http://goo.gl/KL7sYL [EDIT: Embedded as an example for the other links]
- AKP-CHP http://goo.gl/6Mm5AJ
- MHP-AKP http://goo.gl/EEK7F6
- CHP-MHP http://goo.gl/q7KWnN
As a last but not least attempt, I blended the parties in different color images produced above [EDIT: BDP recolored to grey]:
For blending, I used ImageMagick software as described here:
convert akpy.png chpr.png -compose blend -define compose:args=70,70 -composite ac.png
convert ac.png mhpb.png -compose blend -define compose:args=40,80 -composite acm.png
convert acm.png bdpg.png -compose blend -define compose:args=25,75 -composite acmb.png
Then increased the saturation of the images.