Pinterest is a popular photo sharing website. Fashion is one the most popular
and content generating category on this platform. Most of the popular fashion
brands 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 the
popular fashion boards to garner enhanced popularity. What properties on these
fashion boards determine their popularity? Can these properties be
systematically quantified? In this paper, we show how social, temporal and
image signals can together help in characterizing the popular fashion boards.
In particular, we study the sharing/borrowing behavior of pins and the image
content characteristics of the fashion boards. We analyze the sharing behavior
using 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 further
study the image based content properties by extracting fashion, color and
gender terms embedded in the pin images. We observe significant differences
across the popular (highly followed or highly ranked by the experts) and the
unpopular (less followed) boards. We then use these characteristic features to
early predict the popularity of a board and achieve a high correlation of 0.874
with low RMSE value. Our key observation is that likes and repin retention
coefficients are the most discriminatory factors of a board's popularity apart
from the usage of various color, gender and fashion terms.Comment: 13 pages,4 figures, 14 tables, THE 13TH INTERNATIONAL AAAI CONFERENCE
ON WEB AND SOCIAL MEDIA (ICWSM-2019