Sentence examples for emotion ratings from inspiring English sources
The "immediate perception" domain was comprised of all five SQ intensity ratings plus the unpleasantness rating (A1); the "emotional response" domain was comprised of all five emotion ratings (A2) (figure 1).
The notion that the SCRs to (very) unexpected chords reflect effects of emotional processing is also supported by the emotion ratings: These ratings showed that excerpts with expected chords differed from those with an unexpected, and even more so from those with a very unexpected chord in terms of emotional valence, arousal, and surprise.
As a reminder, for emotion ratings, participants who say they use a password manager were asked to rate how they feel while using their password managers.
Physiological activation was recorded during exposure with emotion ratings collected following the film.
We performed Mann–Whitney U tests to evaluate the differences in emotion ratings between the two groups.
Motivated by prior work that has argued that emotions are an important aspect of decision-making [9], we analyze emotion ratings from "users" and "non-users".
Theunissen, Vogels, Koopman, Verrips, Zwinderman, and Verloove-Vanhorick [ 13] found that parent-child agreement was related to child's age and their positive emotions ratings.
Women are generally better at expressing emotions, tend to score higher on emotional ratings on, e.g., neuroticism [ 73] and have an increased risk of suffering from mood disorders.
The selection of these adjectives was derived from the results of a factorial analysis with the various emotion-rating terms used in the work of Zentner and colleagues (see Zentner et al. 2008).
To this end, word categories with low emotional ratings were introduced and the category of emotion words was split into subgroups with and without sensorimotor semantic links.
The basic model examined the effect of the independent variables (stimulus emotion, stimulus authenticity, and cue type) on the response variable (whether emotion rating was correct or not), with participant and speaker repetition included as random effects [glmer(Rating~Emotion * Authenticity * Cue + (1|Participant) + (1|Repetition))].
