They vote as the country: swing communities and electoral polarization

Development, Elections, National elections, Research

Authors: Andriy Gorbal, Andriy Protsyuk, (Ukrainian Center for Social Data), Yevhen Buderatsky (Ukrainska Pravda)

Polarization has always been a distinguishing feature of the Ukrainian elections; people voted en masse for different candidates in the East and in the West. It’s not a geographic characteristic unique to Ukraine; you can compare it to election results in neighboring Poland. At the same time national results in Ukraine were often close to 50/50 (especially in  2004 and 2010).

In order to show that electoral division in Ukraine we developed an interactive tool together with Ukrainska Pravda within the Electoral memory project. It shows not just numbers of votes given to particular candidates in particular localities, but rather how election results in communities differed from the average Ukrainian results.

To see the map in details click here.


The administrative division in Ukraine underwent changes; that’s why we used borders of new Amalgamated Territorial Communities as of 2020 for the map with data consolidation. The old borders of village, town, and city council jurisdiction as of 2014 were used only for Crimea. The first thing you notice is that the 2004 presidential election and parliamentary elections of 2006 and 2007 were the most polarized (we compared results of the first round of the presidential election and a proportional part of the parliamentary elections); while presidential elections of 2014 were the least polarized.


Deviation of presidential election results in communities from the national results in 2004-2019 (darker color represent greater deviation).

In simple terms, the darker color on the map is the greater is the difference of the locality from the national results. It means that a reasonable part of the voters may not be satisfied with election results in such “darker” regions.

Winner Mode

This brings up a question: are there communities who always vote for winners? In other words are there communities who usually vote for parties or candidates winning at the national scale?

Considering a winner only, there were totally 4 such communities during 9 national elections:

  • Kolomatske village community, Poltava Rayon, Poltava Oblast
  • Bashtanka town community, Mykolaiv Oblast
  • Tyahynka village community, Beryslav Rayon, Kherson Oblast
  • Hornostayivka village Community, Kakhovka Rayon, Kherson Oblast

The greatest number of communities who usually voted for winners (7 to 9 coincidences) is in Kherson, Mykolaiv and Kirovohrad oblast. Communities that most of the time voted for candidates losing at the national scale (1 to 3 coincidences) are usually found in Chernihiv, Vinnytsa and Lviv Oblast.

It is also worth mentioning those communities who are close to each other geographically and by other characteristics and may influence each other’s choice.

By other characteristics we mean the level of economic development, employment structure, average age of population, ethnic composition, historical considerations, and some other local factors (a popular local politician, administrative resource and so on).

In the interactive visualization there is a mode Composition of Winners where you can generate maps of communities whose winning candidate coincided with a national winner in 1 to 9 occasions:


It is worth noting that within the new administrative and territorial structure there is no community in Ukraine who had not voted for a winner at least once.

At the same time there are only two communities where national winners won only once; those are the Ponornytsa village community of Novhorod-Siverskyi Rayon in Chernihiv Oblast and Sary-Bash village Council of Pervomaysk Rayon in Crimea.

  • Ponornytsa village community of Novhorod-Siverskyi Rayon in Chernihiv Oblast

  • Sary-Bash village Council of Pervomaysk Rayon in Crimea (data for elections before 2014 only)

Deviation mode

This mode shows the difference between election results at the community and national level in percentage points.  It does not show a leading candidate or party in the community; it shows how different community results of all candidates from the national results are.

Higher numbers reflect higher deviation from national results.

If you look at the average results for all elections starting from 2004 you will see that communities whose election results are close to the national ones tend to be in the South, Center and North of Ukraine.


Top-40 communities (marked in red) with the lowest deviation from the national results (average figures for national elections).

Top-10 communities with the lowest deviation (in percentage points):

Novohuivynske Village Community, Zhytomyr Rayon, Zhytomyr Oblast 14.51
Kremenchuk Town Community, Kremenchuk Rayon, Poltava Oblast 16.44
Chornobaivka Village Community, Kherson Rayon, Kherson Oblast 18.36
Oleshky Town Community, Kherson Rayon, Kherson Oblast 19.38
Hola Prystan Town Community, Skadovsk Rayon, Kherson Oblast 19.6
Kolomatske Village Community, Poltava Rayon, Poltava Oblast 20.24
Myropil Village Community, Zhytomyr Rayon, Zhytomyr Oblast 20.6
Stanislav Village Community, Kherson Rayon, Kherson Oblast 20.64
Bashtanka Town Community, Bashtanka Rayon, Mykolaiv Oblast 20.8
Oleksandriya Town Community, Oleksandriya Rayon, Kirovohrad Oblast 21.03

Novohuivynske Village Community can serve as an example. Their voting results during all elections are surprisingly close to national results.

However, most of the deviations from the national results are found in Donbas:

Svitlodarsk Town Community, Bakhmut Rayon, Donetsk Oblast 100.94
Yenakiyeve Town Community, Horlivka Rayon, Donetsk Oblast 102.08
Vuhlehirsk Town Community, Horlivka Rayon, Donetsk Oblast 102.2

The majority of communities with the highest deviation from the average Ukrainian results are in temporarily occupied territories of Donetsk and Luhansk oblasts; for them we have only data from 2004-2012 when the highest electoral polarization was noted.

Top-40 communities with the highest deviation from national results (average figures for national elections 2004-2019)

The Svitlodarsk Town Community with the highest deviations is used for comparison:

However, the maximum value (more than 80 percentage points) were noted not only in Donbas but also in Crimea and Odessa Oblast (communities near Transnistria and Moldova) as well as in Galicia (communities in suburbs of Lviv) especially during 2004-2012 elections.

Odessa Oblast

Bolhrad Town Community, Bolhrad Rayon, Odessa Oblast 90.2
Kubey Village Community, Bolhrad Rayon, Odessa Oblast 90.89
Velykoploske Village Community, Rozdilna Rayon, Odessa Oblast 92.01
Horodnye Village Community, Bolhrad Rayon, Odessa Oblast 97

Lviv Oblast

Zymna Voda Village Community, Lviv Rayon, Lviv Oblast 88.6
Obroshyne Village Community, Lviv Rayon, Lviv Oblast 89.73
Sokilnyky Village Community, Lviv Rayon, Lviv Oblast 89.84

Combination Choice Mode

It is possible to find communities where different candidates during different elections won: first Yushchenko, next Yanukovych, and then Tymoshenko.

The Combination Choice Mode allows you to filter communities with a certain combination of winners during different elections.

Polarization dynamics or the average value of deviations from the national results in communities show that most of the deviations were noted during the parliamentary elections of 2006 while the lowest number of deviations was noted during the presidential elections of 2014.

The average value of deviations from the national results in communities in percentage points.

It is worth mentioning that 2006 and 2014 elections took place after Maydan revolutions; however, in the first case the internal political disputes resulted in even higher electoral polarization then during the Orange Revolution, while in the second case under the threat of the external enemy the electoral polarization was the lowest in history.


Generally, Ukrainian elections in 2004 – 2019 show that some polarization has always been present. There are geographical, historical, economic, and ethnic reasons for that; at the same time those reasons were deliberately used by political forces to increase polarization.

However, if we match the data with the political situation we can see that in hard historical times when there is an external threat Ukrainians are able to compromise and with effective political communication and sustainable economic development all differences become secondary. It all depends whether politicians are able to articulate a common strategic agenda that would make backslide impossible.