کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
892568 914088 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Could intensity ratings of Matsumoto and Ekman’s JACFEE pictures delineate basic emotions? A principal component analysis in Chinese university students
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب رفتاری
پیش نمایش صفحه اول مقاله
Could intensity ratings of Matsumoto and Ekman’s JACFEE pictures delineate basic emotions? A principal component analysis in Chinese university students
چکیده انگلیسی

Matsumoto and Ekman’s Japanese and Caucasian facial expressions of emotion (JACFEE) have been tried in many countries including China. Consistent results from these nominal (or categorical) studies have been shown that the perception accuracies of Anger, Disgust, Happiness and Sadness are high, and that of Contempt is low, and those of Fear and Surprise are mixed. We have hypothesized that a principal component analysis (PCA) on the perceived intensity alone might offer a scalar (dimensional) classification of emotion. We therefore invited 200 Chinese university students who were blind to the JACFEE nominal classification, to rate the emotion intensities displayed by each poser. Happiness received the highest intensity score, and Contempt the lowest. PCA results produced seven scalar factors of emotion which corresponded well to the nominal ones. Picture loadings on the target emotions demonstrated that Contempt emerged as an independent factor, similarly to Anger, Disgust, Happiness and Sadness. However, picture loadings in regard to Fear and Surprise were mixed up, which still leaves the question open how to separate the two emotions efficiently. Nevertheless, our study has been demonstrated the validity of JACFEE in Chinese culture, and suggests a modification of the picture clusters, especially those of Fear and Surprise.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Personality and Individual Differences - Volume 46, Issue 3, February 2009, Pages 331–335
نویسندگان
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