Special attention to the phenomenon of bloc politics dates roughly from the ascendancy of the General Assembly over the Security Council after 1950, and the consequent importance of votes in the General Assembly.
![voting blocs examples voting blocs examples](https://1.bp.blogspot.com/-QQPb9FdTl7c/VyngPBoduGI/AAAAAAAAAg8/cm3vahcG9tgt2SZ_ERcsb8STPFLWRl7cQCKgB/s1600/inc.png)
This could tell us that nations in voting blocs are more likely to get through the semi-finals.The existence of blocs in the General Assembly of the United Nations and the importance of their activities have been widely recognized ever since its establishment. These nations do not need to qualify for the final through competing in the semi-finals. Interestingly, the big 5 and Australia are in these 15 nations. To address this, I repeated all the steps to produce the first heatmap, but this time I removed the 15 most asymmetric nations. By forcing these nations into voting blocs, we add a lot of noise to the clustering which, in turn, adds a lot of uncertainty to the blocs that we have found. They don’t give points back to the nations that give them points. Some nations have very high measures of asymmetry. This highlights an issue with trying to fit all nations into blocs. If we Look at the geography of the Iberia/Germany bloc, it isn’t too surprising that isn’t a strong voting bloc. Blocs with high Asymmetry are poor examples of voting blocs. ‘Asymmetry’ of 0 would imply that a nation gives back the same points that it receives from a nation. The ‘Asymmetry’ metric tells us how reflected points given and received are. The regional bias in the ‘Northern Europe’ bloc, while above the mean across all nations, is far lower than seen in other areas. When the blocs are ordered together we get this heatmap: This lets us use the Louvain Method for community detection to separate all the nations into voting blocs. The matrix can be seen as a weighted bi-directional network between all the nations. Years in which a nation could not be given points because they didn’t qualify for the final were ignored. I compiled the data into a 2D matrix by averaging the proportions of points given to each nation each year. Nations who received no points in the finals were removed.This removes the weighting towards ranks 1st and 2nd. The point values 12 and 10 were changed to 10 and 9, respectively.So, in years where a nation’s song is ranked poorly overall, their voting bloc will stand out as a large proportion of their points. Nations in a voting bloc will vote for each other regardless of the song quality. The point values given to a nation are divided by the total number of points the nation received that year.With data in hand, I can walk you through the preprocessing steps I decided to use:
#Voting blocs examples code
However, it is missing a couple of years of televoting, so see my Github repository for the data I used and to view the code I created for this post. A lot of the relevant data can be found here.
![voting blocs examples voting blocs examples](https://republican-win.com/wp-content/uploads/2020/08/new-u-s-citizens-were-one-of-the-fastest-growing-voting-blocs-but-not-this-year.png)
Now that this dataset has grown, we have a unique opportunity to identify national bias within the Eurovision watching population of Europe.īefore we can get started, we need a dataset. The competition does attempt to offset political voting by using an impartial jury to hand out half of each nations points, however, Since 2014, the Eurovision song contest has been releasing the televoting rankings of each nation. Voting pairs like Greece and Cyprus or Sweden and Denmark are well known but does this bias go deeper? Can we identify entire voting blocs in the contest? For a long time, the Eurovision Song contest has been accused of political voting.