¿Qué dirían? Prediciendo Comentarios de Usuarios en Pinterest (What Would They Say? Predicting User's Comments in Pinterest)

Juan Carlos Gomez (jcgcarranza@gmail.com)1, Tatiana Tommasi (ttommasi@cs.unc.edu)2, Susana Zoghbi (susana.zoghbi@cs.kuleuven.be)1, Marie Francine Moens (sien.moens@cs.kuleuven.be)1

1KU Leuven
2UNC Chapel Hill

This paper appears in: Revista IEEE América Latina

Publication Date: April 2016
Volume: 14,   Issue: 4 
ISSN: 1548-0992

When we refer to an image that attracts our attention, it is natural to mention not only what is literally depicted in the image, but also the sentiments, thoughts and opinions that it invokes in ourselves. In this work we deviate from the standard mainstream tasks of associating tags or keywords to an image, or generating content image descriptions, and we introduce the novel task of automatically generate user comments for an image. We present a new dataset collected from the social media Pinterest and we propose a strategy based on building joint textual and visual user models, tailored to the specificity of the mentioned task. We conduct an extensive experimental analysis of our approach on both qualitative and quantitative terms, which allows to assess the value of the proposed approach and shows its encouraging results against several existing image-to-text methods.

Index Terms:
Multimodal Clustering, Pinterest, Social Media, User Generated Content, Deep-Learning Representation   

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