The pictures we like are our image: continuous mapping of favorite pictures into self-assessed and attributed personality traits

Segalin, C., Perina, A., Cristani, M. and Vinciarelli, A. (2017) The pictures we like are our image: continuous mapping of favorite pictures into self-assessed and attributed personality traits. IEEE Transactions on Affective Computing, 8(2), pp. 268-285. (doi: 10.1109/TAFFC.2016.2516994)

Abstract

Flickr allows its users to tag the pictures they like as “favorite”. As a result, many users of the popular photo-sharing platform produce galleries of favorite pictures. This article proposes new approaches, based on Computational Aesthetics, capable to infer the personality traits of Flickr users from the galleries above. In particular, the approaches map low-level features extracted from the pictures into numerical scores corresponding to the Big-Five Traits, both self-assessed and attributed. The experiments were performed over 60,000 pictures tagged as favorite by 300 users (the PsychoFlickr Corpus). The results show that it is possible to predict beyond chance both self-assessed and attributed traits. In line with the state-of-the art of Personality Computing, these latter are predicted with higher effectiveness (correlation up to 0.68 between actual and predicted traits).

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Vinciarelli, Professor Alessandro
• Authors: Segalin, C., Perina, A., Cristani, M., and Vinciarelli, A.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: IEEE Transactions on Affective Computing
• Publisher: IEEE
• ISSN: 1949-3045
• Published Online: 12 January 2016
• Copyright Holders: Copyright © 2015 IEEE
• First Published: First published in IEEE Transactions on Affective Computing 2016
• Publisher Policy: Reproduced in accordance with the publisher copyright policy