A Provisional Taxonomy of Subjectively Experienced Positive Emotions

Abstract

Over the past two decades, scholars have conducted studies on the subjective experience of over 30 positive emotional states (see Weidman, Steckler, & Tracy, 2017). Yet, evidence from research on the non-verbal expression and biological correlates of positive emotions suggests that people likely experience far fewer than 30 distinct positive emotions. The present research provided an initial, lexically driven examination of how many, and which, positive emotions cohere as distinct subjective experiences, at both the state and trait levels. Four studies (including two pre-registered replications) using factor and network analyses of 5939 participants' emotional experiences, elicited through the relived emotions task, found consistent evidence for nine distinct positive emotion states and five distinct traits. At both levels, many frequently studied positive emotions were found to overlap considerably or entirely with other ostensibly distinct states in terms of the subjective components used to describe them, suggesting that researchers currently study more positive emotions than individuals experience distinctively. These findings provide the first-ever comprehensive portrait of the taxonomic structure of subjectively experienced positive emotions, with the ultimate aim of inspiring further examination of the positive emotion space at the subjective experiential as well as more biological and behavioral levels of analysis.

Keywords: Emotion; Positive emotion; Subjective experience; Taxonomy.

Fig. 1

Network depiction of higher-order state positive emotions (Study 1). Each node represents one positive emotion. Each line represents a correlation between emotions. Green lines indicate positive correlations, red lines indicate negative correlations, and line thickness indicates the magnitude of correlations (thicker lines indicate larger correlations). The position of the nodes within the network is based on an algorithm which causes strongly correlated emotions to cluster in the middle and emotions with weaker correlations to be located more peripherally (Fruchterman & Reingold, ; see also Borsboom & Cramer, 2013). This note applies to Figs. 1–8

Fig. 2

Network depiction of 17 individual state positive emotions (Study 1)

Fig. 3

Network depiction of higher-order state positive emotions (Study 2)

Fig. 4

Network depiction of 17 individual state positive emotions (Study 2)

Fig. 5

Network depiction of higher-order trait positive emotional dispositions (Study 3)

Fig. 6

Network depiction of 17 individual trait positive emotions (Study 3)

Fig. 7

Network depiction of higher-order trait positive emotional dispositions (Study 4)

Fig. 8

Network depiction of 17 individual trait positive emotions (Study 4)