Chic or Social: Visual Popularity Analysis in Online Fashion Networks Kota Yamaguchi1 Tamara L. Berg2 Luis E. Ortiz1

1Stony Brook University 2University of North Carolina at Chapel Hill

Popularity

Tags

Image Date

Social data

26 Friends 29 Following 552 Followers

Comments •  kool look, love

the hair •  Great look! •  great ...

100 101 102 103 104100

101

102

103

104

105

Popularity measure

Num

ber o

f pos

ts

votescommentsbookmarks

Predicted popular

Predicted NOT popular

Application •  Automatic style

feedback •  Estimating

unbiased rating •  Web-traffic

estimation •  Trend analysis

Can we reason about the votes?

www.chictopia.com

In-network popularity Out-of-network popularity

0 5 10 15 20 250

200

400

600

BinaryTop K

•  Chictopians’ votes •  Social network •  328K posts

•  Crowdsourced votes (AMT) •  No social network •  3,000 posts x up to 25 votes

Modeling posts – how much does each factor matter?

100 101 102 103 104 105 106100

101

102

103

104

105

Number of connections

Num

ber o

f use

rs

friendsfollowersfollowees

Social factors Content factors Other •  User identity •  Previous posts •  Node degrees

•  Date bias •  Tag TF-IDF •  Color entropy •  Image composition •  Style descriptor

mean-std pooling

key points

State-of-the-art computer vision feature

RGB color Lab color MR8 texture Boundary distance Skin-hair detection

328K fashion blog posts

In-network Out-of-network Regression R2 Prediction accuracy Reg. R2 Prediction accuracy

Votes Log-votes Top-25% Top-75% Top-25% Top-75% Social 0.372 0.491 0.847 0.779 0.423 0.845 0.787

Content 0.142 0.252 0.782 0.736 0.395 0.869 0.836 Both 0.341 0.493 0.844 0.776 0.475 0.884 0.857

•  Significant social influence in network but not necessarily out of network. •  Are social and content evaluating different aspect of posts? •  Predicting top pictures are consistently easier than not popular pictures.