%A Garrido,Margarida V. %A Prada,Marília %D 2017 %J Frontiers in Psychology %C %F %G English %K facial expressions,normative data,subjective ratings,emotion labeling,sex differences %Q %R 10.3389/fpsyg.2017.02181 %W %L %M %P %7 %8 2017-December-19 %9 Original Research %+ Dr Margarida V. Garrido,Instituto Universitário de Lisboa (ISCTE-IUL), CIS – IUL,Portugal,margarida.garrido@iscte-iul.pt %# %! Ratings of Angry, Neutral and Happy Faces %* %< %T KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces %U https://www.frontiersin.org/articles/10.3389/fpsyg.2017.02181 %V 8 %0 JOURNAL ARTICLE %@ 1664-1078 %X The Karolinska Directed Emotional Faces (KDEF) is one of the most widely used human facial expressions database. Almost a decade after the original validation study (Goeleven et al., 2008), we present subjective rating norms for a sub-set of 210 pictures which depict 70 models (half female) each displaying an angry, happy and neutral facial expressions. Our main goals were to provide an additional and updated validation to this database, using a sample from a different nationality (N = 155 Portuguese students, M = 23.73 years old, SD = 7.24) and to extend the number of subjective dimensions used to evaluate each image. Specifically, participants reported emotional labeling (forced-choice task) and evaluated the emotional intensity and valence of the expression, as well as the attractiveness and familiarity of the model (7-points rating scales). Overall, results show that happy faces obtained the highest ratings across evaluative dimensions and emotion labeling accuracy. Female (vs. male) models were perceived as more attractive, familiar and positive. The sex of the model also moderated the accuracy of emotional labeling and ratings of different facial expressions. Each picture of the set was categorized as low, moderate, or high for each dimension. Normative data for each stimulus (hits proportion, means, standard deviations, and confidence intervals per evaluative dimension) is available as supplementary material (available at https://osf.io/fvc4m/).