The bright side of words: Norms for 9000 Spanish words in seven discrete positive emotions

Abstract

In recent years, assumptions about the existence of a single construct of happiness that accounts for all positive emotions have been questioned. Instead, several discrete positive emotions with their own neurobiological and psychological mechanisms have been proposed. Of note, the effects of positive emotions on language processing are not yet properly understood. Here we provide a database for a large set of 9000 Spanish words scored by 3437 participants in the positive emotions of awe, contentment, amusement, excitement, serenity, relief, and pleasure. We also report significant correlations between discrete positive emotions and several affective (e.g., valence, arousal, happiness, negative discrete emotions) and lexico-semantic (e.g., frequency of use, familiarity, concreteness, age of acquisition) characteristics of words. Finally, we analyze differences between words conveying a single emotion ("pure" emotion words) and those denoting more than one emotion ("mixed" emotion words). This study will provide researchers a rich source of information to do research that contributes to expanding the current knowledge on the role of positive emotions in language. The norms are available at https://doi.org/10.6084/m9.figshare.21533571.v2.

Keywords: Amusement; Awe; Contentment; Emotional ratings; Excitement; Positive emotions; Relief and pleasure; Serenity.

Fig. 1

Layout of the rating screen for the word descansar (to rest) and the emotion placer (pleasure)

Fig. 2

Correlogram between discrete emotion ratings, dimensional ratings, and other psycholinguistic variables. Crossed out values indicate non-significant values at a significance level of .05. All N = 9,000, except for familiarity (N = 5690), AoA (N = 4875), concreteness (N = 5701), and SER (N = 4437)

Fig. 3

Heatmap depicting the pattern of mixing between positive emotions. Diagonal shows the proportion of words considered "mixed" for that emotion. Each row refers to the words with the highest score in a particular emotion (e.g., contentment in the last row). Numbers indicate the proportion of words which are mixed with other emotions. Note that the sum of the proportions (e.g., 0.3, 0.46, 0.52, 0.55, 0.54, and 0.6) is higher than the proportion of mixed words (0.82). The reason is that words can score high in two, three, four or even more emotions

Fig. 4

The graph depicts the relationship between mean word ratings for each discrete positive emotion and mean scores in the dimensions of valence and arousal

Fig. 5

Scatterplot of the coordinates resulting from the MDS. Two example words are included for each emotion