NYFW: Instagram May Be Able To Predict Fashion Week’s Top Models


Instagram could help predict the industry's next top model, according to a recent study. 

Researchers at Indiana University University have predicted the popularity of new faces to the world of modeling with over 80 percent accuracy using advanced computational methods and data from Instagram, CBS News reported.

"Social media is changing the game dramatically," Giovanni Luca Ciampaglia, a postdoctoral researcher at the Center for Complex Networks and Systems Research and an assistant research scientist at the IU Network Science Institute, said in a statement. "Traditionally, models don't interact with consumers; but now their online activity plays an important role in popularity and, ultimately, success."

For the study, the research team gathered statistics on 400 fashion models from the Fashion Model Directory, a major database of professional female fashion models, tracking hair and eye color; height; hip, waist, dress and shoes size; modeling agency; and runways walked.

They then analyzed the models Instagram accounts, using the social media platform to catalog each user's number of followers, number of posts per month, number of "likes" and comments on those posts, and whether these comments were generally positive or negative. Data for the study was collected in fall 2014.

To test their ability to predict a model's popularity, the researchers narrowed their focus to 15 models listed on the Fashion Model Directory as "new faces," The Dispatch Times reported. Of the eight models expected to achieve the greatest popularity, six were accurately identified. Of the seven predicted to score lowest in popularity, six were also accurately identified.

"Popularity" was defined as the number of runway walks in which a new model participated during the Fall/Winter 2015 season in March.

When analyzing the more established model's Instagram accounts, researchers found that a high number of likes and comments, as well as frequent posting, were associated with success on the runway, although the tone of the comments did not affect popularity. A higher than average number of posts yielded a 15 percent higher chance of walking a runway, but, surprisingly, more "likes" could lower these chances by about 10 percent.

"When we added the social information, we realized that we will be able to predict with above 80 percent accuracy whether a new face, a new model that just started ... would become popular, would run some top runway in the immediate future," Emilio Ferrara, a computer scientist at the University of Southern California, told CBS News.

The focus on "new faces" was an attempt to overcome the powerful influence of "cumulative advantage" on popularity, Ciampaglia added. Researchers also refer to this as the "Matthew effect," a reference to Matthew 13:12, "Whoever has will be given more."

He pointed to Kendall Jenner, the increasingly famous sister of reality star Kim Kardashian, as a poster child for this effect.

"We chose the fashion industry for this research because it represents a strong 'winner-take-all' mentality," Ferrara said. "This aspect of survival of the fittest, plus the large amount of statistical data on professional models, makes it a perfect subject for advancing research on 'the science of success.'"

The findings will be presented at the 19th Association for Computing Machinery conference on Computer-Supported Cooperative Work and Social Computing, taking place Feb. 27 to March 2 in San Francisco.

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