Y U No Go Viral: The Emerging Science of Memes

It's a meme-eat-meme world out there: For one to become popular, another must pass into obscurity.

Bauckhage et al.

More and more of the things that set the internet on fire are of that species of charmingly moronic pairing of text and image that allows even the post-literate to feel like they have partaken of a shared cultural moment. And now, scientists are beginning to understand how the curiously addictive visual tropes known as "memes" are born, why they die, and whether or not it's possible to predict which will "go viral" and be harvested by the night-soil merchants up at meme warehouses like Cheezburger.

Treating memes like genes tells us which are likely to spread
The internet, of course, was barely in its infancy when Richard Dawkins, a British evolutionary biologist, coined the term "meme" back in 1976. And he meant it as a much more nuanced concept, encompassing pretty much any idea that is good at propagating from one human brain to another -- whether it is dialectical materialism or the tune to Happy Birthday.

But Dawkins was deliberate in his comparison of memes to genes. Like the molecular units of inheritance, memes "reproduce" by leaping from one mind to another, "mutate" as they are re-interpreted by new humans, and can spread through a population. The internet has radically accelerated the spread of memes of all kinds; but it has also led to the rise of a specific kind of meme, the kind encapsulated by a phrase or a picture. And importantly for scientists, the life of a such a meme is highly measurable.

New research from Michele Coscia of Harvard University goes so far as to suggest a decision tree -- which is sort of like a flow chart -- that can show at any given point in an internet meme's life how likely it is to go viral. In order to generate this chart, Coscia tracked 178,801 variants of 499 memes, all gathered from what is arguably the internet's biggest clearinghouse for memes, Quickmeme.


Michele Coscia

This decision tree is a bit challenging to parse, but here goes. The number at the top, 35.47%, is the total proportion of all the memes Coscia analyzed that were "successful." By his definition, success meant receiving a high enough score on Memebase, where users can vote a meme up or down. (His threshold for "success" was necessarily somewhat arbitrary.)

Among these successful memes, an interesting phenomenon emerges. Those that hit an above-average peak of popularity at some point in their life were less likely, overall, to ultimately break the "success" threshold. Memes that were shared more consistently over time, rather than a great deal all at once, were more likely to ultimately rack up enough points.

In the attention economy, memes do battle to the death
If you think Nature is red in tooth and claw, you have yet to stare longingly at a website's analytics dashboard, quietly willing an article you wrote to go viral. (Not that anyone at Quartz has ever done this.) In the attention economy, memes compete for a finite pool of attention, representing all the time everyone spends on the internet. Which means that for one meme to become popular, some other meme must pass into obscurity.

Coscia's data crunching revealed that memes that were "more competitive" than others -- that is, whose rise in popularity tended to correlate with the fall in popularity of other memes -- were more likely to succeed overall.

Presented by

Christopher Mims is the science and technology correspondent for Quartz. His work has appeared in Wired and Scientific American, as well as on the BBC.

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