Tag Recommendations in Social Media for Popularity Boosting

Abstract

Researches have shown that well tagged images are more likely to become popular, because it makes them more accessible to other users by adding as many tags as possible. However, it is not an easy task for users to annotate their content with tags that are capable of attracting popularity. Thus in this paper, we propose an recommendation approach which recommend tags that have high influence over popularity, rather than merely semantics and descriptive annotations. We then evaluate the proposed method and several existing tag recommendation strategies on a dataset of Flickr and make a comparison in both efficiency of popularity boosting and tag quality.