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There is growing concern that over the past decade, industrialized democraticnations are becoming increasingly politically polarized. Indeed, elections inthe US, UK, France, and Germany have all seen tightly won races, with notableexamples including the 2016 Trump vs. Clinton presidential election and theUK's Brexit referendum. However, while there has been much qualitativediscussion of polarization on key issues, there are few examples of formalquantitative assessments examining this topic. Therefore, in this paper, weundertake a statistical evaluation of political polarization forrepresentatives elected to the US congress on key policy issues between2021-2022. The method is based on applying sentiment analysis to Twitter dataand developing quantitative analysis for six political groupings defined basedon voting records. Two sets of policy groups are explored, includinggeopolitical policies (e.g., Ukraine-Russia, China, Taiwan, etc.) and domesticpolicies (e.g., abortion, climate change, LGBTQ, immigration, etc.). We findthat out of the twelve policies explored here, gun control was the mostpolitically polarizing, with significant polarization results found for allgroups (four of which were P < 0.001). The next most polarizing issues includeimmigration and border control, fossil fuels, and Ukraine-Russia.Interestingly, the least polarized policy topics were Taiwan, LGBTQ, and theChinese Communist Party, potentially demonstrating the highest degree ofbipartisanship on these issues. The results can be used to guide future policymaking, by helping to identify areas of common ground across political groups.

Quantifying polarization across political groups on key policy issues using sentiment analysis