What makes YOU laugh?

posted Jul 11, 2014, 7:51 AM by Dana Boebinger

We have had three wonderful work experience students in our lab for the past two weeks, and they've written a great piece on the work they've been doing for some of our laughter research:

Figure 1- Participants’ answers to the question ‘what makes you laugh?’ The bigger the word, the  more frequently mentioned it was. 

When we secured a work experience placement at UCL, we expected to receive menial tasks, for example having to make tea or coffee and photocopying. Yet on the very first day of our placement we were handed 2 carrier bags, full of pieces of paper with the word poo (alongside creative doodles) on them. This was the data collected by the laughter lab, who have been investigating over the last few years what made people laugh. 

The results were gathered in July 2012 and March 2013, which essentially gave us a snapshot of that period. The high frequency of Miranda [Hart] could possibly be due to the peaked interest in 2012 after the 3rd series of her self-titled show was released [1].  Similarly, the Harlem Shake [2] went viral in early February 2013, which could explain why quite a few people submitted the dance meme as a suggestion. Another unexpected answer was Mr Bean; which we initially thought was due to the young age of our demographic. We later realised that in July 2012, he performed in the Opening Ceremony of the London 2012 Olympics [3], viewed by 27 million UK viewers. It is fair to assume that our results are somewhat dependent on popular culture events of the time.   

Figure 2- Percentage of categories once the answers had been classified. 

Our transcriptions were put into various categories depending on what they entailed. Each transcription was tagged with a maximum of 3 key words. For example ‘Dad falling over’ was categorised as ‘friends/family’ and ‘schadenfreude’.  Others were harder to categorise such as people just writing “everything” – we classed these as anomalous results and ignored them, excluding them from our final results. After our initial classification, we refined our data by reducing the amount of categories we had. For example we originally had ‘injury’ and ‘violence’ as two separate categories and we later decided to merge them into ‘schadenfreude’. 

We have sorted through data ranging from ‘flowers and snowflakes under a microscope’ to ‘Sachin’s coconut head’. These suggestions and others lacked sense and so were harder to classify; we assumed they were private jokes thus tagging them as ‘jokes’ and a number were censored due to inappropriate content. Several participants also wrote down what they liked rather than what triggered laughter within them i.e ‘I love One Direction’. A handful of answers referred to other answers such as an arrow pointing upwards or ‘this’. Due to not having the original layout of the boards, these answers could not be used in our final data. 

If you look at figure 3, common answers included celebrities such as actors, Youtubers and comedians. 38% of celebrities mentioned were comedians, with the jolly Miranda Hart dominating this category. One of the most interesting findings was the significant number of people whose laughter was provoked by social interaction. For example it is quite clear from the figure 1 that ‘friends’ and ‘people’ appeared as the majority. This is further reinforced by the high percentage (24%) of answers that were categorised into ‘friends/family’. 

Many, it seemed, gained pleasure from seeing people fall over. In fact 75% of answers classed as ‘schadenfreude’ was along the lines of witnessing someone fall over in public. The only real deviation was ‘baby horse falling over.’ Out of all these, only one explicitly said falling people are only funny if ‘no serious injury’ is involved. So are we to assume the other 89 would only laugh if the fall resulted in a horrific facial disfigurement or similar injuries? Some involved close relatives or friends yet most were generalised as ‘people’. One went far enough to paint a picture of an ‘overly-fake tanned fat woman falling off the escalators.’ No matter how childish we may think it is, it seems watching someone fall over is a laughter inducing image.  

Although we had a large sample size (of over 3000), it was clear our key demographic was young teenagers and children, whom attended these conventions. This led to a significant percentage of ‘jokes’ being something that triggered laughter. Therefore, it is not representative of all the groups that make up the population however it can be seen as an accurate interpretation of the various triggers of laughter. 

It is safe to say that being a part of this experiment and collating this mass of data definitely ranks higher than our expectations of acting as general dogsbodies for two weeks. However we still hold the belief that we would have made excellent photocopiers.

Lucy Kent, Haafizah Khodabocus and George Ponniah                                                                                       

Work experience students from Graveney School



[1] Miranda Hart http://www.youtube.com/watch?v=HFUj5GqTArU

[2] Harlem Shake http://www.youtube.com/watch?v=iGCy2zp4XuA

[3] Mr Bean Olympic Cameo http://www.youtube.com/watch?v=BSg_AvqF0qU