The dynamics of attention in social media tend to obey power laws. Attention concentrates on a relatively small number of popular items and neglecting the vast majority of content produced by the crowd. Although popularity can be an indication of the perceived value of an item within its community, previous research has hinted to the fact that popularity is distinct from intrinsic quality. As a result, content with low visibility but high quality lurks in the tail of the popularity distribution. This phenomenon can be particularly evident in the case of photo-sharing communities, where valuable photographers who are not highly engaged in online social interactions contribute with high-quality pictures that remain unseen. We propose to use a computer vision method to surface beautiful pictures from the immense pool of near-zero-popularity items, and we test it on a large dataset of creative-commons photos on Flickr. By gathering a large crowdsourced ground truth of aesthetics scores for Flickr images, we show that our method retrieves photos whose median perceived beauty score is equal to the most popular ones, and whose average is lower by only 1.5%.

An Image Is Worth More than a Thousand Favorites: Surfacing the Hidden Beauty of Flickr Pictures

SCHIFANELLA, ROSSANO;
2015-01-01

Abstract

The dynamics of attention in social media tend to obey power laws. Attention concentrates on a relatively small number of popular items and neglecting the vast majority of content produced by the crowd. Although popularity can be an indication of the perceived value of an item within its community, previous research has hinted to the fact that popularity is distinct from intrinsic quality. As a result, content with low visibility but high quality lurks in the tail of the popularity distribution. This phenomenon can be particularly evident in the case of photo-sharing communities, where valuable photographers who are not highly engaged in online social interactions contribute with high-quality pictures that remain unseen. We propose to use a computer vision method to surface beautiful pictures from the immense pool of near-zero-popularity items, and we test it on a large dataset of creative-commons photos on Flickr. By gathering a large crowdsourced ground truth of aesthetics scores for Flickr images, we show that our method retrieves photos whose median perceived beauty score is equal to the most popular ones, and whose average is lower by only 1.5%.
2015
International Conference on Web and Social Media (ICWSM)
Oxford, UK
May 26-29
Proceedings of the Ninth International Conference on Web and SocialMedia, ICWSM 2015, University of Oxford, Oxford, UK, May 26-29,2015
AAAI Press
397
406
978-1-57735-733-9
http://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/view/10547
Rossano Schifanella; Miriam Redi; Luca Maria Aiello
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1579186
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