Ecole d'ingénieur et centre de recherche en Sciences du numérique

Looking good with Flickr faves: Gaussian processes for finding difference makers in personality impressions

Xiong, Xiaoyu; Filippone, Maurizio; Vinciarelli, Alessandro

MM 2016, ACM on Multimedia Conference, October 15-19, 2016, Amsterdam, The Netherlands

Flickr allows its users to generate galleries of "faves", i.e., pictures that they have tagged as favourite. According to recent studies, the faves are predictive of the personality traits that people attribute to Flickr users. This article investigates the phenomenon and shows that faves allow one to predict whether a Flickr user is perceived to be above median or not with respect to each of the Big-Five Traits (accuracy up to 79\% depending on the trait). The classifier - based on Gaussian Processes with a new kernel designed for this work - allows one to identify the visual characteristics of faves that better account for the prediction outcome.

Document Doi Bibtex

Titre:Looking good with Flickr faves: Gaussian processes for finding difference makers in personality impressions
Mots Clés:Personality; Social Media; Computational Aesthetics
Type:Conférence
Langue:English
Ville:Amsterdam
Pays:PAYS-BAS
Date:
Département:Data Science
Eurecom ref:5018
Copyright: © ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MM 2016, ACM on Multimedia Conference, October 15-19, 2016, Amsterdam, The Netherlands http://dx.doi.org/10.1145/2964284.2967253
Bibtex: @inproceedings{EURECOM+5018, doi = {http://dx.doi.org/10.1145/2964284.2967253}, year = {2016}, title = {{L}ooking good with {F}lickr faves: {G}aussian processes for finding difference makers in personality impressions}, author = {{X}iong, {X}iaoyu and {F}ilippone, {M}aurizio and {V}inciarelli, {A}lessandro}, booktitle = {{MM} 2016, {ACM} on {M}ultimedia {C}onference, {O}ctober 15-19, 2016, {A}msterdam, {T}he {N}etherlands}, address = {{A}msterdam, {PAYS}-{BAS}}, month = {10}, url = {http://www.eurecom.fr/publication/5018} }
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