The LDOS-PerAff-1 corpus of facial-expression video clips with affective, personality and user-interaction metadata
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We present the LDOS-PerAff-1 Corpus that bridges the affective computing and recommender system research areas, which makes it unique. The corpus is composed of video clips of subjects' affective responses to visual stimuli. These affective responses are annotated in the continuous valence-arousal-dominance space. Furthermore, the subjects are annotated with their personality information using the five-factor personality model. We also provide the explicit ratings that the users gave to the images used for the visual stimuli. In the paper we present the results of four experiments conducted with the corpus; an affective content-based recommender system, a personality-based collaborative filtering recommender system, an emotion-detection algorithm and a qualitative study of the latent factors.