Scientists have developed a computer algorithm that predicts whether a
photo will go viral on Facebook by watching how fast it is shared.
Stanford
researchers said the clues to predicting which of the many millions of
photos on Facebook will spring from obscurity and go viral lie in
'cascades'.
The term 'cascades' is used to describe photos or videos being shared multiple times.
"It
wasn't clear whether information cascades could be predicted because
they happen so rarely," said Jure Leskovec, assistant professor of
computer science.
According to data provided by Facebook
scientists in a recent collaboration with university scientists, only 1
in 20 photos posted on the social network gets shared even once. And
just 1 in 4,000 gets more than 500 shares - a lot but hardly an
epidemic.
In a paper to be presented at the International World
Wide Web Conference in Seoul, Korea, the researchers will describe how
they accurately predicted, 8 out of 10 times,
when a photo cascade
would double in shares; that is, if a photo got 10 shares, would it get
20? If it got 500, would it reach 1,000, and so on?
The team
including Leskovec, Stanford doctoral student Justin Cheng, Facebook
researchers Lada Adamic and P Alex Dow, and Cornell University computer
scientist Jon Kleinberg began by analysing 150,000 Facebook photos, each
of which had been shared at least five times.
The data were stripped of names and identifiers to protect privacy.
A
preliminary analysis of those photos revealed that, at any given point
in a cascade, there was a 50-50 chance that the number of shares would
double.
The scientists then looked for variables that might help
them predict doubling events more accurately than a coin toss, including
the rate and speed at which photos were shared, and the structure of
sharing (photos reposted in multiple networks proved to create stronger
cascades).
After factoring several criteria into their analysis
the computer scientists were able to accurately predict doubling events
almost 80 percent of the time.
Their algorithm became more
accurate the more times a photo was shared. For photos shared hundreds
of times, their accuracy rate approached 88 percent.
The speed of
sharing was the best predictor of cascade growth. Simply analysing how
quickly a cascade unfolded predicted doublings 78 percent of the time.
"Slow, persistent cascades don't really double in size," Leskovec said.
How
a photo was shared - scientists call this the structure of the cascade -
was the next best predictive factor. Photos that spread among different
friendship networks or fan groups indicated a breadth of interest.
Structure proved 67.1 percent accurate at predicting doubling when used alone.
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