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29 Apr 2014

How to Know if Your PHOTO Will Be 'LIKED'...study reveals!!

What determines Your Photo's Popularity on social Media


Social media can be a funny place. Why does
one post spread like wildfire, while another
languishes in obscurity?




The science behind a post's popularity has
understandably gotten a lot of attention of late – for businesses investing in social media
advertising, it's important to know that
statistically, a post that includes an image
uploaded on a Friday will provide the highest
engagement rate.


Images, of course, aren't created equal. A recent study by researchers at Georgia Tech analyzed 1.1 million randomly selected Instagram photos and found that those with human faces had a 38 percent greater chance of being 'liked,' and were 32 percent more likely to get comments.


A new study out of MIT gets even more granular. Researchers, led by Aditya Khosla, analyzed 2.3 million Flickr photos to develop an algorithm that can reliably predict how many times a photo will be viewed based on social context
(how many followers a user has) and the image's content.


The algorithm factors in variables including color (warm, bright shades like yellow and pink draw more views than cool, soft tones) and the type of object featured.

Unsurprisingly, sexy images attract the most eyeballs



Miniskirts, bikinis, bras, and revolvers
significantly increased a photo's popularity, the
study found. Plungers, laptops and golfcarts, on the other hand? Not so much.)
While an image's content matters, social context still carries more weight when predicting popularity.


"Overall, popularity is a difficultmetric to understand precisely based on image
content alone because social cues have a large
influence on the popularity of images," the
authors wrote. In other words, a picture of a
plunger posted by a user with thousands of
followers will probably still get more views than an image of a bikini-clad girl posted by a user with five.


You can analyze your unpublished photos using a prototype on Khosla's research page, which measures an image's potential popularity on a
relative scale from one to 10. It's a relatively
crude measurement, but Khosla and his team
plan to refine the algorithm.


"From an application standpoint, is there a
photography popularity tool that could be built
here?" they wrote. "Can photographers be aided
with suggestions on how to modify their pictures
for broad appeal vs artistic appeal?"
Khosla has already developed a similar product .


Last year, he was part of the research team that
created an algorithm able to automatically
modify actors' headshots in order to make the
photos more memorable.

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