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Beyond Knee-Jerk Partisanship? Clinton, Trump, and Speeches

Hillz and The Donald: Speaking of morality and hitting low notes

Quick! How negative was Donald Trump’s nomination acceptance speech? Was it 90% negative, 10% negative, or somewhere in between?

It was about 10 days ago now, but even if you didn’t actually see it you probably heard something about it on the news or around the water cooler. I’ll show you what some numbers say about that and Hillary Clinton’s speech in a minute.


My last couple of posts looked at The Donald’s tweet rhetoric in terms of how he measures up to charges of tyranny and how he compares to Clinton in terms of the way he uses morality-laced words.

And Clinton’s and Trump’s recent nomination acceptance speeches give another opportunity to do a nice apples-to-apples comparison of the language of the parties’ fearless leaders. Trump accepted the Republican Party’s nomination for president Thursday, July 21, from Cleveland in front of 34.9 million TV viewers; Clinton did the same for her party a week later from Philadelphia in front of 33.3 million TV viewers.

I’m a political scientist, so I felt an obligation to watch, which I did as best I could. I follow presidential campaigns fairly closely and tire of knee-jerk partisanship pretty quickly, so watching yet another regurgitation of their rotting red meat can be tedious for me. I usually consider it a success if I can stay awake through the entire thing.

But I was interested in how their acceptance speeches compared in terms of morality as discussed in my last post. Recall that Moral Foundations Theory indicates morality has five universal foundations or concerns:

  • care/harm
  • fairness/cheating
  • loyalty/betrayal
  • authority/subversion
  • sanctity/degradation

Research shows that political conservatives and liberals tend to focus on different foundations. Conservatives tend to focus more on the last three, while liberals tend to focus on the first two. My post analyzing a random selection from one year’s worth of tweets from Hillz and The Donald shows she is fairly consistent with the expectations for political liberals, but particularly focusing on care/harm, while he is not terribly consistent with expectations for political conservatives, although his use of authority/subversion language did stand out.

I conducted the same analysis on their nomination acceptance speeches using the same morality measures and tools (see my previous post if you’re interested in analysis details). And there are some differences.

The graph shows that the moral language Clinton used in her acceptance speech was much more evenly distributed across four of the five moral foundations (light blue bars; ranging from 22% to 26%; both candidates mostly avoid sanctity/degradation-based language) than in her tweets (dark blue bars). It’s not clear why the big shift, but one explanation may be a classic change in audience from the primary election constituency—hard-core, partisan Democrats—to a less partisan general election constituency—“liberalish” voters nationwide.

Gregg R. Murray
Source: Gregg R. Murray

Trump’s speech language, too, seems more evenly distributed across the care/harm, loyalty/betrayal, and authority/subversion foundations (light red bars; ranging from 29% to 32%) than his tweets (dark red bars); although, unlike his tweets, he relied much less on the fairness/cheating foundation. I haven’t convinced myself of any particular explanation for this shift other than in the primary he was more concerned about the fairness of the nomination process, which became a moot issue once he received the nomination that night.


Did you estimate the negativity of Trump’s acceptance speech like I asked? No guts, no glory…

 1845-1915) [Public domain], via Wikimedia Commons
Source: William Richard Gowers (Life time: 1845-1915) [Public domain], via Wikimedia Commons

I’m not sure what post-speech analyses you heard, but I watched most of his speech and then proceeded to watch a cable news talking head declare that Trump’s “relentlessly dark,” “Mad Max America” “terrified” him. And while the analyses I watched the next day were a bit less attention grabbing, they weren't by much. And I began to wonder if I’d been overtaken by the partisan tedium and actually fallen asleep during his speech without knowing it.

So I actually measured the negativity of the speech to see what I’d missed (or what the talking heads had heard). In particular, I used the “Positiv” and “Negativ” (you'd think Ivy leaguers could spell) dictionaries of positive (1915 words) and negative (2291 words) outlook words provided by Harvard.

I readily admit this is not a terribly sophisticated approach to sentiment analysis, but it should show if The Donald was way out of line with his rhetoric. And, just for fun, I’m including the 1980 nomination speech of Ronald Reagan, to whom many political pundits like to compare all Republican presidential nominees, because he was a noted orator and too was running to replace a Democratic incumbent president.

The raw numbers are: Trump 41% negative, Clinton 36% negative, and Reagan 37% negative. Trump’s more negative, as shown in the graph.

Gregg R. Murray
Source: Gregg R. Murray

Umm…does the tone of Trump’s speech compared to Clinton’s and Reagan’s “terrify” you? Or does it appear to be “relentlessly dark” compared to the other two?

Surprised by these numbers? I bet some knee-jerk partisans are.

- - - - - For more Moral Foundations Theory at “Caveman Politics” - - - - - - - - -

“Comparing Morality: Clinton and Trump Tweets Head to Head”

“Is Trump a Tyrant? What His Tweets Say”

"Which of the 5 Types of Political Moralizer are You?"

"Which of the 5 Political Moralizers are PT Blog Readers?"

"Could Disgust Make You an Environmentalist?"

"Are You Easily Disgusted? You May Be a Conservative"

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In addition to writing the "Caveman Politics" blog for Psychology Today, Gregg is the Executive Director of the Association for Politics and the Life Sciences and Associate Professor and Chair of Political Science at Augusta University. You can find more information on Gregg at or follow him on Twitter at @GreggRMurray.

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