1 00:00:04,880 --> 00:00:07,080 Speaker 1: Hey, and welcome to the short Stuff. I'm Josh, and 2 00:00:07,120 --> 00:00:11,039 Speaker 1: there's Chuck and we have one word for you, buddy wiggle. 3 00:00:13,840 --> 00:00:21,200 Speaker 1: Here's another one, Chuck. Poop. That's a genuine laugh. Always 4 00:00:21,200 --> 00:00:23,720 Speaker 1: gets me. Poop is just funny. It is funny. It's 5 00:00:23,920 --> 00:00:27,560 Speaker 1: literally a funny word. Um. And this episode we're talking 6 00:00:27,920 --> 00:00:32,120 Speaker 1: about a guy named Chris Westbury who is a researcher 7 00:00:32,200 --> 00:00:36,040 Speaker 1: out of the University of Alberta, a psychologist actually, and 8 00:00:36,080 --> 00:00:38,360 Speaker 1: he wanted to figure out what makes things funny and 9 00:00:38,400 --> 00:00:42,040 Speaker 1: specifically what makes some words funnier than others. And apparently 10 00:00:42,400 --> 00:00:45,560 Speaker 1: he was a bit of a math genius as a child, 11 00:00:45,720 --> 00:00:49,000 Speaker 1: really got into the statistical analysis kind of stuff, and 12 00:00:49,040 --> 00:00:52,879 Speaker 1: he's applied that as an adult in a study that 13 00:00:52,960 --> 00:00:55,600 Speaker 1: has one of the better names of any study ever published. 14 00:00:56,240 --> 00:00:58,720 Speaker 1: Are you setting me up? I am, Yeah. It was 15 00:00:58,760 --> 00:01:04,280 Speaker 1: called Wrigglely Squiffy lummocks and boobs colon what makes some 16 00:01:04,400 --> 00:01:08,240 Speaker 1: words funny? And this is just super interesting to me too, because, 17 00:01:09,400 --> 00:01:12,039 Speaker 1: like we were talking about, with the nounds of assemblage, 18 00:01:12,480 --> 00:01:15,520 Speaker 1: words and etymology really interests me, and comedy interests me. 19 00:01:15,600 --> 00:01:18,360 Speaker 1: And even though I've never done stand up, I know 20 00:01:18,440 --> 00:01:21,800 Speaker 1: that comedians take a lot of great care with not 21 00:01:21,840 --> 00:01:23,960 Speaker 1: only the bits and the flow and the tone, but 22 00:01:24,319 --> 00:01:28,199 Speaker 1: specific words are funnier than others and can really punch 23 00:01:28,280 --> 00:01:32,080 Speaker 1: up a joke. Agreed, And it says here in this house, 24 00:01:32,080 --> 00:01:36,520 Speaker 1: stuff works article a word like Schenectady or Rancho, cucamonga 25 00:01:36,640 --> 00:01:41,120 Speaker 1: or kalamazoo or just kind of funny words. And this 26 00:01:41,200 --> 00:01:45,360 Speaker 1: guy went out to figure out why. Yeah, he said why. 27 00:01:45,640 --> 00:01:47,920 Speaker 1: People said, who cares, it's it's just funny. Don't look 28 00:01:47,960 --> 00:01:50,400 Speaker 1: too deeply into it. And he said, no, I'm gonna 29 00:01:50,400 --> 00:01:52,880 Speaker 1: do the opposite of that. You will sit there and 30 00:01:52,960 --> 00:01:55,560 Speaker 1: listen when I explain it to you through Josh and Chuck. 31 00:01:55,920 --> 00:01:58,840 Speaker 1: That's right. So what he did was he started off 32 00:01:58,960 --> 00:02:00,920 Speaker 1: with and this is gonna get it really kind of 33 00:02:01,200 --> 00:02:05,120 Speaker 1: not fun at all in a minute. But he started 34 00:02:05,120 --> 00:02:08,160 Speaker 1: off with a list of five thousand English words that 35 00:02:08,600 --> 00:02:10,880 Speaker 1: were rated funniest by people. I guess he did a 36 00:02:10,919 --> 00:02:15,200 Speaker 1: poll or something. And then he constructed a mathematical model 37 00:02:15,919 --> 00:02:19,959 Speaker 1: for predicting which one's uh what what would be funny 38 00:02:20,040 --> 00:02:23,160 Speaker 1: for every single word, like a ranking I guess for 39 00:02:23,280 --> 00:02:26,120 Speaker 1: every single word in the dictionary. Yeah, this model he 40 00:02:26,200 --> 00:02:28,680 Speaker 1: came up with it's kind of complex, it's multi layered. 41 00:02:28,760 --> 00:02:31,919 Speaker 1: It's kind of like an onion, and he basically now 42 00:02:31,960 --> 00:02:35,000 Speaker 1: came run any any word through it. It's okay, he 43 00:02:35,080 --> 00:02:39,400 Speaker 1: can run the The onion is hilarious, but um, he 44 00:02:39,440 --> 00:02:42,919 Speaker 1: can run any word through it and basically spit out like, ah, 45 00:02:43,600 --> 00:02:48,239 Speaker 1: I guess a ranking, how funny? I guess yeah, how 46 00:02:48,280 --> 00:02:51,840 Speaker 1: funny that that word will probably be received? Right, And 47 00:02:51,880 --> 00:02:55,200 Speaker 1: this is all English words specifically, But he came up with, 48 00:02:55,280 --> 00:03:00,400 Speaker 1: based on this mathematical model, the ten funniest words, one 49 00:03:00,440 --> 00:03:05,040 Speaker 1: of which we probably shouldn't even say. Yeah, I guess so, 50 00:03:05,120 --> 00:03:14,799 Speaker 1: but hey man, first amendment, All right up, chuck, yeah, funny, bubby, bof, 51 00:03:16,120 --> 00:03:27,840 Speaker 1: wriggly yaps, giggle, chuck, no, no, no, no, no, cooch, guffaw, puffball, 52 00:03:28,880 --> 00:03:31,760 Speaker 1: and jiggly. Right, so those are the tin funniest. The 53 00:03:31,840 --> 00:03:35,880 Speaker 1: runners up were squiffy, flappy and bucko and buck is 54 00:03:35,920 --> 00:03:41,800 Speaker 1: a great one, poop, puke and boobs got you just now, 55 00:03:42,080 --> 00:03:47,680 Speaker 1: it just got you just. I mean, it's funny. Poop 56 00:03:47,800 --> 00:03:51,600 Speaker 1: is funny the same reason farting is funny. Yeah, the 57 00:03:51,600 --> 00:03:54,360 Speaker 1: word fart is funny. Far the word fart is funny, 58 00:03:54,440 --> 00:03:57,600 Speaker 1: but it's also like shame inducing, you know, like it 59 00:03:57,640 --> 00:03:59,920 Speaker 1: really makes you feel really bad about yourself when you 60 00:04:00,160 --> 00:04:03,080 Speaker 1: use it, right, Yeah, I mean it might just be me, 61 00:04:03,440 --> 00:04:07,360 Speaker 1: but poop basically, no one feels bad for saying the 62 00:04:07,400 --> 00:04:10,920 Speaker 1: word poop, and it is just a genuinely funny word. Yeah. 63 00:04:11,000 --> 00:04:13,640 Speaker 1: And I'll also mention that farting is the one thing 64 00:04:13,720 --> 00:04:16,800 Speaker 1: that allows me to hold on to the fact that 65 00:04:16,839 --> 00:04:20,240 Speaker 1: there may be a God, that there are far yeah, 66 00:04:20,240 --> 00:04:22,279 Speaker 1: and that that God has a sense of humor because 67 00:04:22,440 --> 00:04:27,599 Speaker 1: the fact that a smelly, flammable gas comes out of 68 00:04:27,640 --> 00:04:32,839 Speaker 1: your butt hole and makes a sound. Yeah, And believe us, everybody, 69 00:04:32,839 --> 00:04:35,920 Speaker 1: we've verified it is flammable. It's one of the greatest 70 00:04:35,920 --> 00:04:40,640 Speaker 1: things about human beings. It's pretty great, you know. Especially 71 00:04:40,720 --> 00:04:45,320 Speaker 1: it's like food goes in. We say poot in our house. Now, 72 00:04:45,680 --> 00:04:48,080 Speaker 1: poot's a good one for obvious reasons, you know what 73 00:04:48,200 --> 00:04:50,960 Speaker 1: I say, of course, or just shoot a duck that's right, 74 00:04:51,920 --> 00:04:54,960 Speaker 1: or just pretend it didn't happen. One of those two. Right. 75 00:04:55,240 --> 00:04:59,320 Speaker 1: So another thing we should mention here is um the 76 00:04:59,360 --> 00:05:02,800 Speaker 1: increm congruity theory, and that is the idea that and 77 00:05:02,839 --> 00:05:05,960 Speaker 1: this is sort of a tried and true comedy virtue 78 00:05:06,000 --> 00:05:10,720 Speaker 1: which is something unexpected will make you laugh. Most times. 79 00:05:10,760 --> 00:05:13,400 Speaker 1: It's when you have an expectation of something and something 80 00:05:13,400 --> 00:05:16,400 Speaker 1: else happens. A lot of good comedy can come from that. 81 00:05:17,040 --> 00:05:19,640 Speaker 1: And I mean that's absolutely the basis of comedy, at 82 00:05:19,680 --> 00:05:24,839 Speaker 1: least as far as like all anecdotal evidence, all um, 83 00:05:25,000 --> 00:05:30,120 Speaker 1: like sensible common sense, which is the most sensible kind 84 00:05:30,960 --> 00:05:33,919 Speaker 1: or the most common kind? Um When you when you 85 00:05:34,000 --> 00:05:36,200 Speaker 1: like you really stop and think about in congruity theory, 86 00:05:36,320 --> 00:05:38,760 Speaker 1: it really really makes a lot of sense, right. But 87 00:05:39,440 --> 00:05:42,080 Speaker 1: Chris Westbury was like, that's all well, and good way 88 00:05:42,080 --> 00:05:44,800 Speaker 1: to go Cicero for coming up with in congruity theory. 89 00:05:44,839 --> 00:05:47,000 Speaker 1: But I like to quantify things, so I'm going to 90 00:05:47,080 --> 00:05:49,520 Speaker 1: do that and we'll be right back to explain exactly 91 00:05:49,560 --> 00:06:10,120 Speaker 1: how we did that. After this, I got a question, 92 00:06:11,200 --> 00:06:14,080 Speaker 1: is Westbury the most interesting guy at the dinner party? 93 00:06:14,160 --> 00:06:16,120 Speaker 1: Or does he make you want to gouge your eyeballs out? 94 00:06:17,120 --> 00:06:19,359 Speaker 1: I he might be listening, so I'm not going to 95 00:06:19,400 --> 00:06:22,320 Speaker 1: answer that question. He's one or the other, right, there's 96 00:06:22,360 --> 00:06:24,160 Speaker 1: no in between. You're either like, oh my god, I 97 00:06:24,240 --> 00:06:26,280 Speaker 1: meant this guy and you wouldn't believe like he's got 98 00:06:26,320 --> 00:06:29,919 Speaker 1: these theories and mathematical things we're following, like we're selling 99 00:06:29,960 --> 00:06:31,919 Speaker 1: off all of our stuff and we're gonna start following 100 00:06:31,960 --> 00:06:34,520 Speaker 1: them around. Or he's like, oh God, give me away 101 00:06:34,520 --> 00:06:36,279 Speaker 1: from this, dude. I just tried to make a fart joke, 102 00:06:36,360 --> 00:06:38,680 Speaker 1: and he tried to explain it to me. Right, let 103 00:06:38,680 --> 00:06:40,799 Speaker 1: me go find somebody who's been on the keyto diet 104 00:06:40,839 --> 00:06:44,160 Speaker 1: for three years and talked to them instead. Oh man, 105 00:06:45,120 --> 00:06:50,000 Speaker 1: that's good. So um, what it is? You know why 106 00:06:50,040 --> 00:06:51,520 Speaker 1: because the letter K is in there and we'll get 107 00:06:51,560 --> 00:06:54,000 Speaker 1: to that in a minute. Totally. But what Chris Westbury 108 00:06:54,040 --> 00:06:56,200 Speaker 1: did was he basically took all these words. I think 109 00:06:56,200 --> 00:06:58,720 Speaker 1: he took um several hundred of him to start, like 110 00:06:58,760 --> 00:07:02,560 Speaker 1: a subset of the was five thousand funniest words, and 111 00:07:02,720 --> 00:07:04,760 Speaker 1: he just kind of took a random subset of him 112 00:07:04,920 --> 00:07:09,000 Speaker 1: and he started analyzing them with a Google tool that 113 00:07:09,120 --> 00:07:12,600 Speaker 1: basically shows co occurrence. Right, So basically you run these 114 00:07:12,640 --> 00:07:16,760 Speaker 1: words through this little Google machine learning algorithm and it 115 00:07:16,880 --> 00:07:20,440 Speaker 1: spits out other words that people have used instead of 116 00:07:20,600 --> 00:07:23,360 Speaker 1: or in conjunction with it, right. And what he figured 117 00:07:23,400 --> 00:07:27,840 Speaker 1: out was that out of like this couple hundred sample set, 118 00:07:29,400 --> 00:07:33,640 Speaker 1: you could basically boil it down to six general categories um, 119 00:07:33,920 --> 00:07:35,880 Speaker 1: and all of the words had something to do with 120 00:07:35,920 --> 00:07:42,480 Speaker 1: either an expletive, being an expletive, um, sex, the body, partying. 121 00:07:42,760 --> 00:07:44,920 Speaker 1: I guess which one just just kind of struck me 122 00:07:44,960 --> 00:07:47,600 Speaker 1: as out of the blue, Um, I was not expecting 123 00:07:47,640 --> 00:07:53,120 Speaker 1: that one. What else, chuck, animals or insults? And so 124 00:07:53,160 --> 00:07:57,760 Speaker 1: those are the six clusters of categories of funny words. Okay, 125 00:07:57,760 --> 00:08:00,240 Speaker 1: so he said, all right, great, but the thing is, 126 00:08:00,560 --> 00:08:03,320 Speaker 1: there's a lot of words that like kind of straddle 127 00:08:03,400 --> 00:08:06,880 Speaker 1: these categories. How can you how can you say, like, 128 00:08:07,200 --> 00:08:09,520 Speaker 1: you know, what makes one funnier than the other? What's 129 00:08:09,560 --> 00:08:12,240 Speaker 1: the deal here? And I'm not sure how he did this. 130 00:08:12,400 --> 00:08:14,440 Speaker 1: I'm not even sure that he knows how he did this. 131 00:08:15,480 --> 00:08:23,200 Speaker 1: But he basically assigned a statistical UM number two a 132 00:08:23,360 --> 00:08:28,120 Speaker 1: word and insofar as it related to its category. Right, 133 00:08:28,200 --> 00:08:34,120 Speaker 1: so like um uh, birthday cake were probably pretty close 134 00:08:34,280 --> 00:08:38,400 Speaker 1: to the party category, like it's it's probably pretty close 135 00:08:38,480 --> 00:08:42,080 Speaker 1: or fete or fiesta or something like that. It's very 136 00:08:42,080 --> 00:08:44,960 Speaker 1: close to its synonymous to a ward in this category. 137 00:08:45,000 --> 00:08:47,200 Speaker 1: But even that didn't quite describe what made a word 138 00:08:47,200 --> 00:08:49,000 Speaker 1: funny and what a guess he figured out And I'm 139 00:08:49,000 --> 00:08:51,839 Speaker 1: not sure how he did this was that the funniest 140 00:08:51,880 --> 00:08:57,480 Speaker 1: words were related, um equally roughly to a number of 141 00:08:57,520 --> 00:09:00,240 Speaker 1: different categories. And it seems like the more that a 142 00:09:00,280 --> 00:09:03,079 Speaker 1: word was related to one or a number of these 143 00:09:03,080 --> 00:09:06,640 Speaker 1: six categories, the funnier it was. And a good example 144 00:09:06,679 --> 00:09:10,480 Speaker 1: he gave was poop right, it's uh it. It can 145 00:09:10,520 --> 00:09:13,880 Speaker 1: be an expletive, it can be um, part of the body, 146 00:09:14,320 --> 00:09:18,080 Speaker 1: it can be a party. Um. There's it has to 147 00:09:18,120 --> 00:09:21,280 Speaker 1: do with multiple categories, and so it's funnier than say, 148 00:09:21,360 --> 00:09:24,320 Speaker 1: fiesta is you know that made sense to me for 149 00:09:24,360 --> 00:09:29,960 Speaker 1: the first time after reading this like seven times, yes, yeah, yeah, yeah, seven, seven, eight, 150 00:09:30,080 --> 00:09:32,719 Speaker 1: ten times maybe yeah. It just the way he was 151 00:09:32,760 --> 00:09:35,040 Speaker 1: putting it never made sense, but you brought it around 152 00:09:35,080 --> 00:09:37,080 Speaker 1: for me. So thank you, thank you, Chuck Man. That 153 00:09:37,120 --> 00:09:40,280 Speaker 1: means a lot to me. So he got to that point, 154 00:09:40,360 --> 00:09:41,840 Speaker 1: but then he said, you know what the meaning of 155 00:09:41,840 --> 00:09:44,440 Speaker 1: these words, that's only one kind of measurement. Everyone else 156 00:09:44,480 --> 00:09:48,880 Speaker 1: was saying, stop, that's good, that's good, you're fine, you 157 00:09:48,920 --> 00:09:51,439 Speaker 1: did it, you did it. But he said, no, no, no, 158 00:09:51,520 --> 00:09:54,200 Speaker 1: that's not enough. Meeting is only one type of measurement. 159 00:09:54,320 --> 00:09:56,160 Speaker 1: And so he said, let's look at and this is 160 00:09:56,160 --> 00:09:58,240 Speaker 1: actually kind of the good part to me, He said, 161 00:09:58,280 --> 00:10:00,000 Speaker 1: we need to look at the form of these words, 162 00:10:00,720 --> 00:10:03,320 Speaker 1: how long they are, the individual sounds that make up 163 00:10:03,360 --> 00:10:07,520 Speaker 1: these words, And that's where incongruity theory of humor kind 164 00:10:07,520 --> 00:10:11,840 Speaker 1: of comes back, because the fewer times that these uh 165 00:10:11,960 --> 00:10:15,160 Speaker 1: phone ms uh, the individual sounds appear like, the more 166 00:10:15,240 --> 00:10:21,560 Speaker 1: rare they are, the funnier that people think they are. Yeah, Like, basically, um, 167 00:10:21,600 --> 00:10:25,760 Speaker 1: I guess K is much The K sound in particular 168 00:10:26,160 --> 00:10:31,280 Speaker 1: is much less um used in English than say, like B. 169 00:10:33,200 --> 00:10:36,480 Speaker 1: So that's why like words with K sounds or are 170 00:10:36,559 --> 00:10:39,320 Speaker 1: funnier than words with say, T sounds. So pickle is 171 00:10:39,360 --> 00:10:43,440 Speaker 1: funnier than tomato, which is we just inherently know. And 172 00:10:43,480 --> 00:10:46,280 Speaker 1: so what Chris Westberry was basically onto is that by 173 00:10:46,360 --> 00:10:50,360 Speaker 1: analyzing the arrangement of letters and how frequently they occur 174 00:10:50,800 --> 00:10:55,040 Speaker 1: in words in the English language, that he tied it 175 00:10:55,080 --> 00:10:59,000 Speaker 1: into that incongruity theory. And he basically said, our brains 176 00:10:59,040 --> 00:11:03,079 Speaker 1: are constantly analyzing the information that's coming in from watching 177 00:11:03,080 --> 00:11:06,000 Speaker 1: TV or talking to people or reading or something like that, 178 00:11:06,280 --> 00:11:10,040 Speaker 1: and we have a certain expectation. And with that expectation, 179 00:11:10,200 --> 00:11:14,720 Speaker 1: isn't met um like something that statistically is improbable like 180 00:11:15,160 --> 00:11:18,440 Speaker 1: the word walla, walla Washington comes up out of nowhere. 181 00:11:18,800 --> 00:11:21,240 Speaker 1: You don't see that every day. You weren't really expecting it, 182 00:11:21,280 --> 00:11:23,600 Speaker 1: and it kind of makes things funny to you because 183 00:11:23,600 --> 00:11:27,600 Speaker 1: it triggers that incongruity response. Yeah, and that your brain 184 00:11:27,720 --> 00:11:29,920 Speaker 1: is you don't know it, but it's constantly doing this 185 00:11:30,000 --> 00:11:33,319 Speaker 1: in the background, and you just here it is funny, right, 186 00:11:33,760 --> 00:11:37,440 Speaker 1: you just you just go walla, walla Washington. So yeah, 187 00:11:37,480 --> 00:11:41,160 Speaker 1: if you're just starting out in comedy, really pay attention 188 00:11:41,200 --> 00:11:43,520 Speaker 1: to the words, and especially the words in the punch 189 00:11:43,559 --> 00:11:48,800 Speaker 1: line because swapping out individual words can make a big difference. Um. 190 00:11:48,920 --> 00:11:51,800 Speaker 1: Can we close with this quote from The Sunshine Boys? Yeah, 191 00:11:51,840 --> 00:11:54,200 Speaker 1: I think so the great. Have you ever seen this movie? 192 00:11:54,760 --> 00:11:57,200 Speaker 1: I have not, man, but I know it's George Burns 193 00:11:57,200 --> 00:11:59,680 Speaker 1: and Walter math Yes, it is the best. It is 194 00:11:59,720 --> 00:12:02,839 Speaker 1: a great movie about this comedy team who hate each 195 00:12:02,840 --> 00:12:05,800 Speaker 1: other's guts and they're old men now and they're trying 196 00:12:05,840 --> 00:12:09,480 Speaker 1: to get them together for a reunion show. So Walter 197 00:12:09,600 --> 00:12:13,440 Speaker 1: math Aw says this, fifty seven years in the business, 198 00:12:13,440 --> 00:12:15,679 Speaker 1: you learn a few things. You know what words are 199 00:12:15,679 --> 00:12:19,360 Speaker 1: funny and which words are not funny. Alka Seltza is funny. 200 00:12:19,920 --> 00:12:23,640 Speaker 1: You say alka seltza, you get a laugh Casey stingle. 201 00:12:24,000 --> 00:12:28,000 Speaker 1: That's a funny name. Robert Taylor is not funny, Cupcake 202 00:12:28,120 --> 00:12:32,720 Speaker 1: is funny, Tomato is not funny. Cleveland is funny, Maryland 203 00:12:32,840 --> 00:12:36,240 Speaker 1: is not funny. And then there's chicken. Chicken is funny, 204 00:12:36,440 --> 00:12:41,040 Speaker 1: Pickle is funny. And he's kind of right. Oh, he's 205 00:12:41,080 --> 00:12:44,400 Speaker 1: beyond kind of right. He's fully right, for sure. Good stuff. 206 00:12:44,679 --> 00:12:48,319 Speaker 1: But just one question. That was your Walter math Now 207 00:12:48,640 --> 00:12:53,320 Speaker 1: that wasn't great. Well, everybody go watch the Sunshine Boys 208 00:12:53,559 --> 00:12:55,560 Speaker 1: and see what Chuck was talking about, and you can 209 00:12:55,600 --> 00:12:57,960 Speaker 1: compare his Walter math out to the real Walter math. Ow, 210 00:12:58,040 --> 00:13:00,320 Speaker 1: how about that? And in the meantime, you can go 211 00:13:00,400 --> 00:13:02,400 Speaker 1: check out this article on how stuff works. Right, Chuck, 212 00:13:02,480 --> 00:13:05,440 Speaker 1: that's right. And in the meantime, meantime, short stuff is out. 213 00:13:08,400 --> 00:13:10,240 Speaker 1: Stuff you Should Know is a production of I Heart 214 00:13:10,280 --> 00:13:13,400 Speaker 1: Radio's How Stuff Works. For more podcasts for my heart Radio, 215 00:13:13,520 --> 00:13:16,360 Speaker 1: visit the iHeart Radio app, Apple Podcasts, or wherever you 216 00:13:16,400 --> 00:13:20,599 Speaker 1: listen to your favorite shows. H