Occasionally something in the news strikes a resonant chord with those with  Conversation Analysis- tuned ears – and the laughter that treated President Trump at the UN on 25th September 2018 was just such an occasion. I’m delighted that Alexa Hepburn has been willing to bring her expertise to bear on a geopolitically sensitive question: was Trump laughed at? Or was the audience laughing with?

There’s a reason that the English language has 50 words for laughter (well, a lot anyway). We can snigger, titter, chortle or chuckle, and giggle, cackle, guffaw and roar. But why? What’s it all for? Enter the conversation analyst!

Careful transcription reveals not simply what type of laughter we’re dealing with, but also facilitates analysis of the actions that it manages and responds to.

The following is a transcript of the 30 seconds in which Donald Trump dealt with audience members’ laughter during his speech to the U.N. General Assembly in New York on the 25th of September 2018. Trump arrived late – he was only leaving Trump Tower when the speech should have started, the schedule was changed to accommodate his lateness.  This might not have endeared his audience to him. We join Trump around 40 seconds in.

[You can see the the video on YouTube by clicking here]

TRUMP UN 25.9.18 0.43-1.09

Trump begins his speech with strong claims about his administration’s achievements on lines 1-3. According to Anita Pomerantz, explicit self-praise is a dispreferred action, though perhaps less avoided in this context where listing one’s country’s achievements might be relevant. However, on line 4 some members of the audience treat Trump’s utterance as laughable – a highly disaffiliative response.

How does Trump deal with the laughter?

In response, Trump cuts off where he was headed on line 5 to gaze at the culprit/s and reiterate his point with a half-smile (line 6). This clearly treats the laughter as undermining the truth of his initial claim – as laughing at. Over the next few seconds, the audience laughter grows louder (line 8). What’s interesting is how Trump deals with this. This time, rather than reiterating his point further, or ignoring it and soldiering on, he issues a sharply exhaled laughter particle on line 9. By laughing right here, Trump is able to recast himself as breaking out of his speech to laugh along with, rather than continue and be laughed at. Further laughter from the audience ensues (line 10).

Using his own laughter to defuse the insult

He continues the break from giving his speech to explicitly attend to the laughter as unexpected – as a dispreferred response, not something he wanted to elicit (line 11). But note that he does this while smiling then laughing himself. In our studies of post completion and interpolated laughter, Chloe Shaw, Jonathan Potter and I often saw it as a way of modulating some problem or insufficiency with the action one has just done, while nevertheless doing it. Without the smiling and laughter line 11 would sound more hurt and reproachful. The loudest audience laughter comes at this point on 13 with some applause – here it is at least partly hearable as appreciation of Trump’s candid and jokily delivered confession. The open-handed gesture indicates Trump’s ‘nothing to hide’ posture.

So was Trump laughed at or was he laughing with?

Trump later told reporters: “Oh it was great. Well, that was meant to get some laughter, so it was great.” I think we can say, looking at his reiteration on line 6, that this is a misleading post hoc reconstruction of what happened here. He also said afterwards at a press conference: “We had fun…So, the fake news said: ‘people laughed at President Trump,’ …They didn’t laugh at me. People had a good time with me. We were doing it together.”

This is to some extent true towards the latter half of this sequence. While Trump at first is clearly laughed at and attempts to reiterate his initial claim on line 6, it’s not clear that later on in the sequence everyone laughed at Trump. His treatment of the laughter from line 9 onwards would have been disarming for some, and it is telling that the loudest laughter and some applause can be heard following his jokey sequence closing turn on line 11. So perhaps the world is not quite as against him as some commentators thought….

Read more about transcription and analysis in Alexa Hepburn and Galina Bolden’s textbook Transcribing for Social Research