Why Jokes Go Viral

Jokes, despite their popularity and widespread sharing across the Internet, are not a new concept. From a very young age we learn the setup of a joke, and very quickly catch on to the pattern of joke telling: someone shares a joke, I find it funny, and days later retell the joke to a group of friends, family or coworkers. Maybe some time later one of them will tell it at a party and the chain goes on. Jokes can play an integral role in socializing; in fact, certain people seem like nothing more than joke perpetuation machines and would be lost without their repeatable nature.

How do they work? Why do we spread them on? And how can I engineer more infectious jokes?


Two fish in a tank.
One turns to the other and says: “Do you know how to drive this?”

The human experience is full of cognitive dissonance and disconnects; incidents where our perception and our reality clash. Evolutionarily, these episodes can be scary at best, and deadly at worst. If you’re not expecting a certain type of berry to be poisonous and you go out and forage them for dinner, perception and reality can very quickly clash in a toxic fashion. Our ancestors lived in constant fear of being the last to know some vital piece of information, and it is scarcity that makes knowledge valuable and contagious; you’re not doing your tribal duty if you don’t tell everyone which berries will kill you.

Urban legends demonstrate a similar trait called delayed orientation. The protagonist is operating under commonly held assumptions: her perception of the scratching on the roof of her boyfriend’s car on that darkened lovers’ lane tells her not to go check it out. In the morning, it turns out it was her boyfriend, hung upside down by the serial killer and she could have saved him–if only that information wasn’t so scarce.

Perception colliding with reality causes goosebumps. And we love sharing goosebumps–they’re contagious.

Jokes address that tension and resolve it in a nonthreatening manner. Remember that swine flu joke graphic with the little kid licking the pig’s nose? Catharsis. See the 1963 Tanzanian contagious laughter outbreak as another example.

A patient says: “Doctor, last night I made a Freudian slip, I was having dinner with my mother-in-law and wanted to say: “Could you please pass the butter.” But instead I said: “You silly cow, you have completely ruined my life.”

If you want to mastermind your own humor pandemic, play on existing incongruities.

Joke Cycles

A joke cycle is a collection of jokes that revolve around a single event, idea or person. They tend to start quickly, in memetic waves, and die unfunny deaths just as soon as they began. Cycle-based jokes often recycle old structures with the new topic; how many times have we heard the same joke, just different names? Cycles commonly address topics of great societal unease like swine flu, celebrity deaths, and the Challenger disaster; they’re like catharsis epidemics.

In 1993’s Healing with Humor, Dr Arthur Asa Berge says “whenever there is a popular joke cycle, there generally is some widespread kind of social and cultural anxiety, lingering below the surface, that the joke cycle helps people deal with.”

In your humor laboratory, base your jokes on those moments of cultural tension.


Before you can retell a joke, you must be able to remember it. Specific details in a joke can help create a mental image of the scene, aiding in recall. However, these minutiae are easy to lose or mutate between tellings–successful jokes don’t depend on fine-grain elements, they are enhanced by them.

The unexpectedness that makes a joke funny can also make it hard to recall, as the human mind finds it easier to store information types we’ve dealt with before. This is why the most clichéd jokes are often the easiest to remember. Contagious and funny jokes frequently make use of a new-old model, where either new content is shoehorned into an old structure, or a old content is reworked into a new structure.

Why did the chicken cross the road?

DR. SEUSS: Did the chicken cross the road? Did he cross it with a toad? Yes, The chicken crossed the road, But why it crossed, I’ve not been told!

KARL MARX: It was an historical inevitability.

BILL CLINTON: I did not cross the road with THAT chicken. What do you mean by chicken? Could you define chicken, please?

ERNEST HEMINGWAY: To die. In the rain. Alone.

State-dependent memory and sensorial triggers can also aid the recall process. Some people have a joke they tell every single time they’re drunk. And some people have jokes they tell every time someone says a certain word or phrase.

Make sure your viral joke is easy to remember.

Social Setting

I always look for a woman who has a tattoo. I see a woman with a tattoo, and I’m thinking, okay, here’s a gal who’s capable of making a decision she’ll regret in the future.

What’s the first thing you do before telling a joke? You look around you. Once you remember a joke, the social setting you find yourself decides if you will tell it. Off-color jokes are the most obvious example, but there are other, more subtle variations exist. People in “high-culture” environments often refrain from telling jokes at all, preferring witty retorts to canned material. Gender often plays a roll as in the stereotype of “ladies who don’t tell jokes and sluts who laugh at dirty jokes.”

Be aware of your target demographics’ social considerations when constructing quips.


Twitter is the perfect petri dish to test out your jokes. Throw a few ideas against the wall and see which are ReTweeted.

If you liked this post, check out the rest of the ProtoViral Posts.

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ReTweets Change Everything

I spend a lot of time working on ReTweets, mostly because I believe them to be one of the most important developments in modern communications, extending far beyond the Twittersphere.

“Ideas shape the course of history.”
-John Maynard Keynes

Ideas have been spreading from person to person for thousands of years; contagious ideas form the very foundation of human culture and history. Like “The Matrix” was composed of computer code, the real world is made of infectious information. Your chair, your desk, the computer you’re reading this on, the food you’ll eat today, the money you’ll earn; they all began as ideas jumping from person to person. None of it would exist if the concept wasn’t contagious.

For the last few millennia people have been telling each other about which god to believe in and which laundry detergent works best.

“There is one thing stronger than all the armies in the world, and that is an idea whose time has come.”
-Victor Hugo

Contagious ideas are the most powerful force in our world. Ideological epidemics have made and lost fortunes, they have saved countless lives and caused horrific wars, they have birthed and destroyed nations. Clearly the most powerful weapon known to man would be the ability to create powerful mental viruses at will. The very course of human history would be at your whim.

And remember, you don’t spread ideas just because they are “good;” you spread them because of some other trigger or set of triggers has been pulled in your brain. And that trigger fires the biggest gun ever seen.

Rudimentary attempts of this sort of engineering have been made to sometimes awe-inspiring ends; however, those successes have most often been based on luck and happenstance.

A reliable, repeatable method to craft a contagious idea has yet to emerge.

“If the Internet can be described as a giant human consciousness, then viral marketing is the illusion of free will.”
-George Pendle

The advent of the web changed how memes spread: it made them spread faster, it exposed them to more people, and it removed many of the constraints imposed by the limits of human memory. Obviously, post-web idea viruses are more contagious. But there is one change that dwarfs them all: observability.

Before we can purposely create a more contagious idea, we have to understand which elements make an idea contagious. The problem has been that for thousands of years there has been no way to observe memes in aggregate. Only anecdotal evidence could be analyzed, and, in areas like urban legends, rumors, and slang, these unreliable sources provided our only clues.

We can now compare millions of viral ideas to uncover the building blocks of contagiousness.

The structure of the web has made this sort of observability possible from a theoretical standpoint for over a decade. ISPs could have tracked email chain letters, or IMs from person-to-person, but technological and privacy issues prevented that.

ReTweets change all of this.

ReTweets may seem like a small idea, and they are. But that small idea is the first real window into how ideas spread from person to person. We can study the linguistic traits, the topical characteristics, the epidemiological dynamics, and the social network interactions that take place when a person spreads a meme.

Not only can this information help us create more contagious Tweets, but many of the lessons learned through ReTweets will be applicable to viral ideas in other mediums.

For the first time in human history we can begin to gaze into the inner workings of the contagious idea. That most powerful force can now be put under our microscope and probed for its secrets.

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The Linguistics of ReTweets

I’ve done a bunch of research into the characteristics of ReTweets in an effort to understand what makes them viral. ReTweets are the first entirely observable and analyzable viral content spreading mechanism in the history of mankind and as such they offer an unparalleled window into what makes humans spread ideas.

Over the past few weeks I’ve begun delving into much deeper analysis than I have in the past with more advanced tools and a much larger dataset. At present I have a database of over 10 million ReTweets and I’ve gained access to Twitter’s new streaming API which allows me to build a very large (10 million and growing) random sample of all tweets (not just ReTweets).

In re-visiting a data point that I looked at 6 months ago (this time with a larger data set), I found that in a random sample of normal (non-ReTweet) Tweets, 18.96% contained a link, whereas 3 times that many ReTweets (56.69%) included a link.



Then I tested the assumption that simplicity is a vital component of ReTweets (as it has been observed in other viral-content types) and I found that random Tweets have 1.58 syllables per word on average, while ReTweets had an average of 1.62 syllables per word. Longer, higher syllable-count words are typically more complex, indicating that ReTweets may be more complex than their less viral counterparts.


Comparing two different types of reading grade level analysis revealed that ReTweets, in general, are less “readable” and require a higher level of education to understand. A Flesch-Kincaid test gave ReTweets a reading grade level of 6.47 years of education, while random Tweets only required 6.04 years. The similar SMOG test (Simple Measure of Gobbledygook) indicated that ReTweets required 6.13 years of schooling, with random Tweets only needing 5.88 years.


Another characteristic commonly found in viral content is novelty; that is, the “newness” of the ideas and information presented. I created a measure of novelty by counting how many other times each word in my sample sets occurred. In the random Tweet sample, each word was found an average of 89.19 other times, while in the ReTweet sample each word was only found 16.37 other times. This shows us that while simplicity may not be very important to ReTweetability, novelty certainly is.


Part of speech (POS) tagging is an analysis technique in which an algorithm is used to label each word in a piece of content as a specific part-of-speech–noun, verb, adjective, etc. The graph below shows what percentages of words in each sample were labeled as a specific part-of-speech. It lists only the most interesting parts from the much larger list of POS tags.

Interesting points from this data include the noun and 3rd-person heaviness of ReTweets, indicating a subject matter and headline type nature.


I also used the two linguistic lexicons currently in use on TweetPsych: RID and LIWC.

First up is the more “Freudian” Regressive Imagery Dictionary (RID). This coding scheme is designed to measure the amount and type of three categories of content: primordial (the unconscious way you think, like in dreams); conceptual (logical and rational thought); and emotional.

Significantly more primordial content has been found in the poetry of poets who exhibit signs of psychopathology than in that of poets who exhibit no such signs (Martindale, 1975).

The first RID graph shows that ReTweets contain less primordial and emotional content than random Tweets and more conceptual content.


Looking at specific RID codes, we see that social and instrumental (constructive words like build and create) behavior are ReTweetable, while abstract thought and sensation-based words are not.


The last analysis I performed used LIWC (pronounced “Luke”). This is a lexicon similar to RID, but based in more reviewed and accepted research and refined over 15 years. LIWC measures the cognitive and emotional properties of a person based on the words they use.

In order to provide an efficient and effective method for studying the various emotional, cognitive, and structural components present in individuals’ verbal and written speech samples, we originally developed a text analysis application called Linguistic Inquiry and Word Count, or LIWC.

LIWC analysis shows that Tweets about work, religion, money and media/celebrities are more ReTweetable than Tweets about negative emotions, sensations, swear words and self-reference.

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