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@ARTICLE{Teijeiro-Mosquera_TAC_2014,
         author = {Teijeiro-Mosquera, Lucia and Biel, Joan-Isaac and Alba-Castro, Jose Luis and Gatica-Perez, Daniel},
       projects = {Idiap, IM2},
          title = {What Your Face Vlogs About: Expressions of Emotion and Big-Five Traits Impressions in YouTube},
        journal = {IEEE Transactions Affective Computing},
           year = {2014},
       abstract = {Social video sites where people share their opinions and
feelings are increasing in popularity. The face is known to reveal important
aspects of human psychological traits, so the understanding
of how facial expressions relate to personal constructs is a relevant
problem in social media. We present a study of the connections between
automatically extracted facial expressions of emotion and impressions
of Big-Five personality traits in YouTube vlogs (i.e., video blogs). We
use the Computer Expression Recognition Toolbox (CERT) system
to characterize users of conversational vlogs. From CERT temporal
signals corresponding to instantaneously recognized facial expression
categories, we propose and derive four sets of behavioral cues that
characterize face statistics and dynamics in a compact way. The cue
sets are first used in a correlation analysis to assess the relevance of
each facial expression of emotion with respect to Big-Five impressions
obtained from crowd-observers watching vlogs, and also as features
for automatic personality impression prediction. Using a dataset of 281
vloggers, the study shows that while multiple facial expression cues
have significant correlation with several of the Big-Five traits, they are
only able to significantly predict Extraversion impressions with moderate
values of R-square.},
            pdf = {https://publications.idiap.ch/attachments/papers/2015/Teijeiro-Mosquera_TAC_2014.pdf}
}