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Pinterest is a popular photo sharing website. Fashion is one the most popularand content generating category on this platform. Most of the popular fashionbrands and designers use boards on Pinterest for showcasing their products.However, the characteristics of popular fashion boards are not well-known.These characteristics can be used for predicting popularity of a nascent board.Further, newly formed boards can organize their content in a way similar to thepopular fashion boards to garner enhanced popularity. What properties on thesefashion boards determine their popularity? Can these properties besystematically quantified? In this paper, we show how social, temporal andimage signals can together help in characterizing the popular fashion boards.In particular, we study the sharing/borrowing behavior of pins and the imagecontent characteristics of the fashion boards. We analyze the sharing behaviorusing social and temporal signals, and propose six novel yet simple metrics:originality score, retention coefficients, production coefficients,inter-copying time, duration of sharing and speed coefficients. We furtherstudy the image based content properties by extracting fashion, color andgender terms embedded in the pin images. We observe significant differencesacross the popular (highly followed or highly ranked by the experts) and theunpopular (less followed) boards. We then use these characteristic features toearly predict the popularity of a board and achieve a high correlation of 0.874with low RMSE value. Our key observation is that likes and repin retentioncoefficients are the most discriminatory factors of a board's popularity apartfrom the usage of various color, gender and fashion terms.

"Woman-Metal-White vs Man-Dress-Shorts": Combining Social, Temporal and Image Signals to Understand Popularity of Pinterest Fashion Boards