Byung-Chul Han and other authors have pointed out that political discourses are undergoing a transmutation from the style prevailing in the 1980s to the current one, where post-truth, emotion and social networks seem to have changed the strategies and discourses of political organizations.

Beyond opinions, I would like to know what quantitative work has been carried out by political scientists to confirm or disprove this type of reflections?

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    I would point to historian Timothy Snyder who had risen to prominence since the Russian invasion of Ukraine. He specializes in Eastern European history which gave him a front row seat to Russia's post-truth society and how it has steadily exported this type of politics to the democratic west in recent years. The core of his analysis revolves around two concepts: "politics of ineveitability" and "politics of eternity" - the later in particular is a type of poltiics that discards truth and favors emotion / spectacle entirely. Commented Jul 10, 2022 at 14:00

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I think this is a bit difficult to answer given that -- even with more language analysis tools -- it's harder to quantify emotions and then take the next step of connecting them to "the strategies and discourses of political organizations". For example, tweets clearly affect politicians and their decision-making however most politicians don't list out the tweets that affected their proposal or vote. The short answer to your question seems to be not much quantitative work.

That being said, I think this is a really interesting topic and did find some slightly more data-driven articles and charts on the subject. If this is in the direction of what you were looking for, I'd be happy to continue updating this list as I (or others) find more...

Note that most of these articles are focused on US politics. That may be because my search results are catered based on where I'm searching from but I think the bigger problem is just that there haven't been many broad or international quantitative studies done.

Key metrics worth considering...

  • Advertising (quantity, audience, medium, spend, emotional content via nlp).
  • Speeches (quantity, audience, medium, emotional content via nlp).
  • Political social media posts (detected via nlp and then measured for sentiment/emotion)

Related articles but not directly containing the quantitative metrics you're looking for...

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