Do People Agree on How Positive Emotions Are Expressed? A Survey of Four Emotions and Five Modalities Across 11 Cultures

The interest in understanding positive emotions is growing with advances in the fields of affective science (Keltner, 2019), and social psychology (Fredrickson, 2001). Previous theorizing and research in which negative and positive emotions were compared has mainly focused on joy (or happiness), which is conceived as a singular emotion argued to be primarily expressed using the face (e.g., Ekman, 1992). However, recent theorizing posits that there are multiple discrete positive emotions (see Shiota et al., 2017) that are expressed through channels that go beyond the face, including postural cues (Dael et al., 2012a, 2012b), the use of words (Campos et al., 2013), displays via touch (Schirmer & Adolphs, 2017), and vocalizations (Sauter & Scott, 2007).

Several accounts have sought to map out how different positive emotions relate to one another and what functions they serve. Whereas none of these accounts yield straightforward predictions of how different positive emotions are expressed, we drew on this work to inform our selection of emotions as well as in the formation of exploratory initial hypotheses. Given the long-running debate in the field with regard to the universality of emotion (e.g., Russell, 1994, and reply by Ekman, 1994), we selected two frameworks that each stem from a different research tradition: the emotion families approach (Sauter, 2017) and the arousal-engagement matrix (Kitayama et al., 2006; Tsai et al., 2006). Emotion families are based on evolutionary functions that are shared across human beings (Tooby & Cosmides, 2008), with a focus on specialised functions for different emotions. The arousal-engagement framework emphasises cross-cultural differences (Boiger & Mesquita, 2012), and posits that emotions can be classified according to underlying dimensions. Although these taxonomies are inspired by divergent lines of work, they are not mutually exclusive, because they each focus on different elements and functions. We first outline these frameworks and the predictions we derived from them, and next specify the modality-specific hypotheses for each of the four positive emotions that are the focus of the present paper.

The emotion families approach (Sauter, 2017) postulates that positive emotions can tentatively be classified into one of four clusters, which diverge in terms of evolutionary functions (for similar suggestions, see Shaver et al., 1987, and App et al., 2011). This classification scheme is informed by work relating to expressions (e.g., Simon-Thomas et al., 2009) and appraisals (e.g., Roseman, 1996). The modalities in which different positive emotions are expressed is thought to map onto the purported function of the cluster in which a given emotion is thought to belong. Epistemological emotions (e.g., interest) involve a change or shift in one’s knowledge state. Congruent with the cognitive nature of such emotions, expressing an epistemological emotion would be likely to involve the use of higher order cognitive processes, such as language (LeDoux & Brown, 2017). Prosocial emotions (e.g., gratitude) focus people towards the welfare of others and help foster social relationships. Expressing prosocial emotions should hence involve affiliative gestures that bring people closer together, which can be expressed through physical contact or verbal signals. Savoring emotions (e.g., feeling moved) stem from experiencing enjoyable, calming, or heartwarming stimuli. Given that such emotions are purportedly linked to unconditioned stimuli that make one feel good, expressions would be likely to include smiling. Finally, agency-approach emotions (e.g., triumph) are characterized by approach tendencies towards potential rewards. Given the need to explicitly display movement towards an objective, such emotions may be likely to involve bodily movement.

In the arousal-engagement matrix, we combine the complementary dimensions of physiological arousal (Tsai et al., 2006) and social engagement (Kitayama, et al., 2006), such that positive emotions could theoretically fit into one of four potential quadrants. Arousal refers to the extent to which an emotion elicits a heightened physiological response in an individual (Larsen & Diener, 1992), while engagement denotes the degree to which an emotion is socially oriented and thereby brings people closer together (Kitayama et al., 2000). Based on this framework, high arousal emotions may involve the recruitment of multiple nonverbal modalities that act as amplifiers to convey the heightened arousal an expresser feels. In contrast, low arousal emotions might involve less nonverbal signals, and a greater reliance on words to express how one feels instead. Socially engaging emotions should be likely to involve the use of signals that clearly display affiliative motives—such as smiling, touch, and words—to bring people closer together and to minimize interpersonal misunderstandings. Conversely, socially disengaging emotions, which increase social distance between oneself and others, should make less use of the abovementioned channels.

Based on these theoretical taxonomies, we selected four positive emotions that varied in terms of emotion family, arousal, and social engagement: feeling moved, gratitude, interest, and triumph. Table 1 lists the four positive emotions we selected in relation to the theoretical frameworks. We also added the modalities through which we expected each emotion to be expressed. These modalities are based on both the characteristics and functions of each of these emotions, according to the theoretical frameworks outlined above, as well as a review of the empirical literature on nonverbal expressions. In the ensuing section, we lay out the rationale for our predictions.

A growing body of empirical work has shown that some specific positive emotions have uniquely distinguishable expressive signals (Keltner & Cordaro, 2017), occurring across multiple channels (Cowen et al., 2019; Elfenbein et al., 2007). In production studies, researchers typically examine how people express positive emotions using one or two modalities (most commonly the face, and to a lesser extent voice). Expressions can be produced spontaneously in ecologically valid scenarios (Tracy & Matsumoto, 2008), with poses in controlled laboratory settings (Cordaro et al., 2018), or elicited with stimuli that are meant to induce specific emotions (Levenson et al., 1991). The expressive cues, such as facial muscle movements or vocalizations, are then empirically mapped using established coding schemes (Dael et al., 2012a, 2012b; Ekman et al., 2002) and automatic detection software using algorithms (Krumhuber et al., 2019; Schuller & Schuller, 2020). A broad range of positive emotions have been found to have specific nonverbal cues (for a review, see Sauter, 2017). For example, amusement is expressed with an open-jaw smile (Ambadar et al., 2009) and vocalizations with multiple amplitude onsets (Sauter et al., 2010), while awe is signaled with raised eyebrows, eye-widening, parted lips (Campos et al., 2013), and visible inhalations (Shiota et al., 2003).

Yet, little research has systematically compared across modalities (see Kessous et al., 2010, and Schirmer & Adolphs, 2017). Our present understanding of positive emotional expressions is based on scattered bodies of work, and many modalities have yet to be considered in relation to specific positive emotions. The empirical findings we review, and our hypotheses for the present research, are consequently constrained by the limitations of this literature. With regards to our four selected positive emotions (feeling moved, gratitude, interest, triumph), some empirical evidence has been put forth that allows predictions to be made about the non-verbal cues used to express each of them. We introduce each of these emotions in turn, and outline the predictions we made for each, along with theoretical and empirical rationales for our hypotheses. In addition, where applicable, we also distinguish between signals and signs (see Sauter & Russell, 2020). Signals are expressive behaviors that are inherently communicative; they purposefully (though not necessarily consciously) convey social information to observers (Fridlund, 1994). In contrast, signs are expressions that are simply “given off” (Goffman, 1959); neither communicative functions nor intentions are necessary components of signs.

Feeling moved is an intense emotion that is triggered when partaking in (or observing) communal sharing relationships, such as an unexpected reunion (Cova & Deonna, 2014). This emotion is thought to be mixed in terms of valence (e.g., bittersweet), in that mostly positive but also negative feelings are elicited when feeling moved (Menninghaus et al., 2015; Vuoskoski & Eerola, 2017). Possibly as a reflection of this negative valence, some empirical evidence points to increased muscular activity around the eyes (e.g., corrugator) when people feel moved (Wassiliwizky et al., 2017a, 2017b; but see Zickfeld et al., 2020). Robust cross-cultural evidence also suggests that feeling moved is displayed and identified via tear droplets and crying (Schubert et al., 2018; Seibt et al., 2018; Zickfeld et al., 2019b). While other modalities have also been suggested to be involved in the expression of feeling moved, such as vocalisations and hand gestures (Fiske et al., 2019; Zickfeld et al., 2019a), these modalities have not consistently been found across studies. The most robust empirical evidence has been found for tears.

In terms of the arousal-engagement matrix, feeling moved is a high-arousal high-engagement positive emotion. Clear communicative signals are to be expected for conveying feeling moved in order to bring others closer to the expresser. This is consistent with empirical work indicating that tears signal a desire for help, and trigger approach orientations in others (Gracanin et al., 2018). In the emotion family framework, being moved is considered a savoring positive emotion. Savoring emotions typically have quite clear displays on the face (Sauter, 2017). In sum, both theoretical and empirical evidence led us to postulate that the face should be the main modality through which feeling moved is expressed.

Gratitude is defined as a feeling of thankfulness and indebtedness for the positive actions and contributions of another person or group (Algoe, 2012). Much of the work on gratitude has focused on verbal rather than nonverbal expressions (Algoe & Haidt, 2009; Algoe et al., 2013), with research showing that when indebted, people express being thankful with words of appreciation (Williams & Bartlett, 2015). There are also findings pointing to gratitude being expressed via handshakes, meaning that touch could be employed in some contexts (Hertenstein et al., 2009). A clear facial expression for gratitude has however yet to be surfaced (Campos et al., 2013), and given the scant attention paid to vocalisations of gratitude (see also Yoshimura & Berzins, 2017), it remains theoretically possible that people may reduce the volume of their voice when they feel grateful.

Gratitude is a low-arousal high-engagement positive emotion. It is thus similar to feeling moved in terms of triggering social orientations. However, gratitude displays would be expected to be less intense in nature, reflecting the comparatively lower state of arousal of the expresser. In term of emotion families, gratitude is a prosocial emotion, which entails communication via touch in order to stimulate closeness and social attachment. This aligns with empirical work as described above (App et al., 2011). However, expressing gratitude through touch (e.g., clasping someone’s hand) also intrudes on the physical space of the perceiver, and so would only be appropriate to use between people who already have a close relationship with one another (Lee & Guerrero, 2001). Taking theory and the contextual nature of empirical findings into account, we therefore expected only words and the voice to be used for expressing gratitude.

Interest is conceptualised as a feeling that arises when new and relevant stimuli are encountered in the environment (Silvia, 2008). It is a multi-faceted emotion, such that expression modalities may depend on the domain of interest (Silvia, 2005). Past work has demonstrated interest to be expressed using a quickened speech rate, and a widened vocal frequency range (Banse & Scherer, 1996). The use of phrases and questions also signal a keenness to engage (Silvia, 2008), indicating that both the voice and words could be key communicative channels for expressing interest. For the facial expression of interest, both signals (constriction of the eyebrows to communicate a deep concentration on a specific topic: Campos et al., 2013; smiling: Mortillaro et al., 2011) and signs (parted lips: Reeve, 1993; widened eyes: Shiota et al., 2003) are postulated to be to be involved. A case has also been made for a body movement sign associated with interest, namely, leaning forward (Dael et al., 2012a, 2012b; Dukes et al., 2017).

Interest is thought to be a low-arousal emotion. This would suggest that interest is not likely to be expressed using the full range of body movements, which would be more likely to characterise emotions that are more intense. In terms of engagement, interest is thought to be malleable; being interested draws one’s attention inwards towards a specific topic (Sung & Yih, 2016), but at the same time, one could also share their interest with others (Yoon et al., 2012; Rime, 2009). The epistemological nature of interest points to the potential use of higher order cognitive processes like language, and so words could be an important communicative tool for expressing interest. Given that a direct comparison between modalities has yet to be made for interest, we postulated the use of modalities that both empirical work and theorising concur with. As such, words, the face, and voice, were all expected to be used to express interest.

Triumph is the feeling elicited upon victory (Matsumoto & Hwang, 2012). Empirical work has suggested that in the immediate aftermath of winning, specific signals emerge: people adopt a straightened body posture with the chest protruding, and make guttural sounds signalling their victory (Tracy & Matsumoto, 2008). There is also evidence from two divergent cultural samples examining athletes immediately post victory, which found that winners tended to show open mouthed smiles and upward head tilting (Hwang & Matsumoto, 2014). Even in work suggesting that victory displays are regulated so as to spare perceivers’ feelings, an expansive body posture comes through as a partially suppressed signal related to winning (Van Osch et al., 2019).

From a theoretical standpoint, triumph is deemed a high-arousal low-engagement emotion. Given high arousal, its expressions should involve the recruitment of multiple expressive channels to demonstrate a larger social presence via expansiveness of the self (App et al., 2011). The dominance focused nature of triumph signals highlights the socially disengaging nature of this emotion (Kalokerinos et al., 2014), and suggests that multiple channels should be involved in its expression. Similar expressive patterns are expected based on triumph being an agency-approach emotion. To signal one’s agency and possibly even power, triumph should involve body postures and head movements that seek to make the self look taller and larger (Hwang et al., 2016). Both theory and empirical work thus point to the hypothesis that triumph should be expressed via body movements, facial expressions, and the voice.

A major caveat to the patterns of expression described above is that the degree to which they generalize to people from most parts of the world is at present unestablished. Much of the empirical research on emotional expressions has thus far been conducted with North American samples (see Keltner & Cordaro, 2017), and even genuine attempts at cross-cultural work are often hampered by the fact that most respondents are university students. Student samples share many common characteristics regardless of which part of the world they come from (Henrich et al., 2010) and are typically not representative of the populations they are thought to reflect. While some researchers have recruited community samples to draw a contrast between modernized and culturally isolated populations, such lines of work have tended to either focus on one specific positive emotion (e.g., Tracy & Robins, 2008), or a particular modality in isolation (e.g., Ekman et al., 1987; Sauter et al., 2010). The need to study community samples across a broad range of cultures, while examining various modalities of expression for different positive emotions, remains a worthwhile endeavour for the advancement of theory in affective science.

For the present research, we adopted an established method from cross-cultural psychology to examine self-reported expressions of positive emotions: the intersubjective approach (Chiu et al., 2010). When applied to emotion expressions, the intersubjective approach entails asking people how other members of their culture in general express specific positive emotions (feeling moved, gratitude, interest, triumph), with commonly used modalities presented as response options (face, voice, body, touch, words).

Self-report instruments provide many advantages for cross-cultural work, especially when contrasted with classic methods from production studies. Many of the existing tools used in expression research are not only costly and time intensive, but also involve the practical constraints associated with setting up on-site data collection in divergent cultural contexts. As a means of navigating such difficulties, other researchers too have employed variants of self-report: respondents choose from photographs that depict various stages of an expression (Matsumoto, 1990; Van Osch et al., 2019), indicate on a mannequin or avatar which parts of the body are most implicated when an emotion is felt (Nummenmaa et al., 2014; Van Cappellen & Edwards, 2020), or recollect emotional experiences and textually describe all components they associate with each specific emotion, including expressions (Campos et al., 2013). These self-report formats facilitate cross-cultural research, because surveys can be conducted wholly online, and thus be used to reach community samples with relative ease and at lower cost than traditional lab studies.

The intersubjective approach deals with two common methodological concerns associated with self-reported emotion expressions: the expectation that participants have accurate insight into how they express different emotions, and the assumption that aggregated individual responses can be taken as a valid reflection of a cultural group’s response patterns. By using the intersubjective approach, we measure expressions from the perspective of the perceiver, thereby capturing estimates of expressions from commonly encountered targets in everyday life. Such items mitigate the need for introspective evaluation by shifting the focus away from one’s own behaviors to observed displays in others. Furthermore, by presenting categorical response options with clear and familiar labels, this approach eliminates culturally-dependent response biases that may occur on Likert-type scales (Van Herk et al., 2004). Because this approach is based on the principle of shared consensus (Wan et al., 2010), culture-level conclusions are drawn based on agreement between raters, rather than simply assuming a given sample’s demographic features and response patterns to be representative of a larger nation unit.

In sum, existing theorizing and empirical work suggest that positive emotions are nonverbally expressed through several different channels, yet to date studies have tended to examine only singular (or maximally two) modalities at a time. Here, we sought to provide a first step towards systematically mapping out which modalities are associated with particular positive emotions across countries that differ on cultural values (Minkov & Hofstede, 2012; Schwartz et al., 2001).

In the present research, we use intersubjective judgments to map out how several positive emotions are thought to be expressed across a wide range of cultures. Specifically, we examine how people perceive others in their culture to express four distinct positive emotions, selected based on the emotion families approach (Sauter, 2017) and the arousal-engagement matrix (Kitayama et al., 2006; Tsai et al., 2006). In three studies, we examined peoples’ perceptions of how others in their culture express feeling moved, gratitude, interest, and triumph. Study 1a was exploratory and mapped out which modalities were most frequently thought to be associated with expressing feeling moved, gratitude, interest, and triumph in the U.S.A. We selected emotions that have been corroborated by past research to have some degree of identifiable expressions in North America (Cowen & Keltner, 2020). This also allowed for a critical evaluation of the intersubjective rating method, where our obtained findings should be in alignment with previous research. Study 1b was a pre-registered replication study with a separate community sample from the U.S.A., which sought to test whether the removal of emotion definitions would shift participants’ responses (see https://​osf.​io/​yrpa4/​?​view_​only=​3d8c542ebdfd47ff​ba126ca96e5ac142​).

Study 2 was cross-cultural and confirmatory, and also pre-registered (see https://​osf.​io/​p7je9/​?​view_​only=​8a8c076d0c974e6b​b6038df06df2b892​). We examined the degree to which our initial predictions would hold across a set of national samples that varied on cultural values. We broadly sampled from multiple regions of the world, where respondent also spoke varying languages (see Table 5 for further information). We here recap our initial exploratory hypotheses for each positive emotion. By predicting that specific modalities would be most frequently reported, we expected those particular modalities to be selected significantly more often than all of the other expressive channels.

All studies reported in this paper received ethical approval from the Department of Psychology at a large European university. For fully anonymized data files, materials, and analysis script, see: https://​osf.​io/​szah4/​?​view_​only=​3270f24f3c704f34​b42d88f574930fa6​

In Study 1a, we mapped out how Americans think four specific positive emotions are expressed. Largely in line with our initial predictions, participants reported that feeling moved is conveyed primarily using the face, gratitude by what someone says and how it is said, interest is communicated using facial expressions, words, and the voice, while triumph was expressed using the face, voice, body, and—contrary to our prediction—words. We interpreted this unexpected finding to be a culture-specific pattern that reflects U.S.A. culture, where verbal expressions of triumph are often encouraged (Hwang & Matsumoto, 2014; Van Osch et al., 2013).

While nearly all of the findings support our predictions, we acknowledge a potential shortcoming of our method. By providing definitions for emotions, we could have unintentionally guided participants to select particular modalities. To rule out this alternative explanation, we conducted a pre-registered replication study with a new sample of participants from the U.S.A.

We replicated our key findings from Study 1a, demonstrating that even when emotion definitions were not provided to participants, the most commonly reported modalities of expressions largely matched our predictions.⁴ In both community samples from the U.S.A., feeling moved was reported to be conveyed primarily using the face, gratitude by what someone says and how it is said, interest via facial expressions, words, and the voice, and triumph using the face, voice, body, and words.

These findings provide consistent evidence for how respondents from one particular country think emotions are expressed. Next, we sought to test the cross-cultural robustness of our findings. The degree to which emotional expressions differ across cultures is a hotly contested topic (see Manokara & Sauter, 2021), and we hence aimed to evaluate whether participants from various parts of the world would also think that positive emotions are expressed with similar modalities as in the U.S.A.

In Study 2, we further mapped out how people report four specific positive emotions to be expressed, with samples from ten countries differing in terms of geographic region and cultural values. The results were highly consistent with those of Studies 1a and 1b, and across the cultural samples. As predicted, feeling moved was thought to be expressed via the face. This finding was consistent across all of the countries, except for China. For gratitude, words were, as hypothesised, deemed the most frequent expressions. Again, this finding was consistent across countries, with the exception of China. We did not find consistent evidence supporting the use of voice as an expressive modality for gratitude. For interest, words, face, and voice were deemed frequent expressions across countries, with some cultural specificities arising in India (where the voice was less frequent) and China (where the face and voice were less frequent than expected). Finally, across countries, triumph was thought to be expressed using facial, bodily, and vocal cues. Moreover, we replicated the finding from Studies 1a and 1b showing that participants thought that triumph was frequently expressed with words.

The present findings provide empirical evidence that highlights contrasting use of different modalities for expressing feeling moved, gratitude, interest, and triumph. These findings were largely replicated across the cultural contexts, and align with theorising about the functions of positive emotions both from the emotion family perspective (Sauter, 2017) and the arousal-engagement matrix (Kitayama et al., 2006; Tsai et al., 2006). The cross-cultural consistency of our findings suggests statistical regularities in the social environments of participants that arguably reflect actually occurring expressions, thereby pointing to potential consistencies in how people from varied cultures express specific positive emotions. To establish whether these patterns are present in actual behaviour will require further study.

Across cultures, participants consistently reported that feeling moved is expressed via the face. This is in line with work suggesting that tears (Schubert et al., 2018; Seibt et al., 2018) are consistent markers of this emotion. Tears signal being overwhelmed (Gracanin et al., 2018), which is a key component of feeling moved. The present findings also align with the high-arousal high-engagement nature of displaying feeling moved. Tears are associated with states of high arousal when experiencing feeling moved, and signal a need for help—thereby drawing others closer for social engagement.

Participants thought that gratitude is primarily expressed with words, as we had hypothesized. However, although we also expected the voice to be used frequently to express gratitude, this was not supported by our findings. The voice was not reported as often as were words, nor was the voice any different in frequency from the face and touch, thereby suggesting that the voice is not a salient a modality for expressing gratitude (see also Floyd et al., 2018). Touch emerged as a quite frequent modality for expressing gratitude, and in some cases (such as the Netherlands and Germany), was second only to words. These findings are in line with past theorising on touch being a key modality for affiliative gestures (App et al., 2011). We did not hypothesize touch as a critical modality given the context-unspecified nature of our measure. We expected touch to emerge as a modality used to express gratitude only when the perceiver was deemed a close other, since touch could also be viewed as a violation of ones’ privacy and space (Lee & Guerrero, 2001). Even though participants made judgments about members of their group in general (without a context specified), touch was often thought to be used for expressing gratitude. This aligns with the expectation that expressions of prosocial positive emotions would include the recruitment of touch.

For interest, words emerged as the most often used modality, with the face also commonly reported. The voice was recruited in many cultures as well, but this finding was less cross-culturally robust than the highly consistent findings for the use of words to express interest. In line with theorising about epistemological emotions, our findings highlight the crucial nature words play in conveying a shift or update in ones’ knowledge state. Furthermore, the low-arousal nature of interest seems well reflected in the fact that bodily movement was not frequently reported as a modality used to express interest, even though some empirical work has suggested that such expressions can occur (Dael et al., 2012a, 2012b).

For expressing triumph, body posture, voice, and the face were all deemed as frequently used modalities, in line with past empirical and theoretical work suggesting that dominance expressions are signalled with expansive gestures that recruit multiple modalities (App et al., 2011; Van Osch et al., 2013). What was surprising, however, was that participants across cultures reported words to be one of the primary ways to express triumph. We initially thought these findings may be specific to the U.S.A., where explicit verbal expressions of victory are encouraged (Hwang et al., 2016). However, this result was consistent across cultural groups, and potentially reflects the fact that our measure did not specify a particular time point for expression. Perhaps participants were thinking about what happens in the aftermath of a victory as well, when social sharing of emotions is common (Rime, 2009).

Our results also point to some culture specific patterns, although it is worth noting that the statistical tests employed were not set up to directly test cross-cultural variability. For example, baseline differences in how many modalities people from divergent cultures select can yield cultural differences. Indeed, the Chinese sample had overall lower response frequencies as compared to the other samples. Nonetheless, we descriptively map out the key cultural specificities found in our data and point to potential theoretical reasons for why these patterns may have been found.⁶

For feeling moved, we did not obtain support in favour of our hypothesis in China, where words were reported as often as the face to express feeling moved. One possible explanation is the existence of strict facial display rules in China. Strong cultural norms might constrict the outward expression of emotions that signal vulnerability via tears (Davis et al., 2012). Previous research has shown strong display rules for expressing sadness in East Asia (Matsumoto et al., 2008), which could generalise to other forms of tear-based expressions as well. In this cultural context, individuals might rely more on words to communicate feeling moved to others.

An interesting pattern emerged for gratitude expressions in India, where the voice was thought to be least frequently used. Unexpectedly, the face, body and touch were all reported to be more frequently used than the voice. These findings could have to do with the relational norms that are prevalent in Indian society, where kinship ties are maintained and fostered through reciprocity and the open expressions of thankfulness (Miller et al., 2017). As such, words could be used alongside other modalities that quite clearly signal being thankful in this cultural context—including the face—which is a primary conveyor of social information and is often used to create and sustain affiliation (Van Kleef, 2009).

Findings for interest in China raise key theoretical questions regarding the classification of interest as a primarily inward-looking (or socially disengaging) emotion (see also Sung & Yih, 2016). In the Chinese context, touch (which could be conceptualised as an affiliative gesture; App et al., 2011) was also recruited for the expression of interest. Perhaps in some cultural contexts, interest could be conceptualised as a socially engaging emotion that is primarily relevant with reference to other people (Silvia, 2005). This line of argumentation fits recent arguments pointing to the role of context in determining the degree to which interest is inward-focused (see also Greenaway et al., 2018).

A key strength of the present research is that we examined expressions from the perspective of the perceiver, thereby circumventing the need for and bias of introspective judgments. Accurate introspection by participants should not be assumed, particularly when expressions can be quick and fleeting, possibly even beyond the threshold of consciousness (Yan et al., 2013). Our use of the intersubjective approach is based not on reports about oneself, but on observations of others, which helps mitigate some of these concerns. Furthermore, the fact that our findings align with the available empirical literature on emotional expressions predominantly conducted in the U.S.A. (Cowen & Keltner, 2020), suggests that our choice of method is appropriate.

Potential limitations of our work relate specifically to the cross-cultural nature of our research. If measures from individuals are considered a reflection of a country’s response patterns, then a large representative sample would be required for an accurate representation of that country. Such sample features may not be achieved if researchers recruit paid participants from online platforms that are microcosms in themselves (see Chmielewski & Kucker, 2020), or hard-to-obtain populations using a convenience snowballing approach.

Furthermore, when using rating scales to contrast between groups, culturally dependent response bias is likely to occur. A growing literature has demonstrated that cultural norms influence response styles in Likert-type items, such as acquiescence bias in countries where deference to authority is valued (e.g., East Asia: Chen et al., 1995), and extreme responding in cultures where amplified expressions are encouraged (e.g., Latin America: Culpepper & Zimmerman, 2006). Such biases undermine the reliability of conclusions researchers can draw from cross-cultural comparisons of intersubjective measures, as genuine differences become conflated with response styles.

The methods we employed deal with these considerations in two main ways. Rather than assuming participants to be prototypical or representative of their culture, the intersubjective approach taps into the shared knowledge and expertise of group members; respondents are hence viewed as experts of their culture due to their lived experiences (Wan et al., 2010). As such, a culture’s pattern of responses is inferred from the degree of agreement between raters. Second, rather than using classic rating scales, we provide categorical response options that are clearly labelled in participants’ native language. We also provided emotion definitions that were closely matched across the languages because we judged it essential to maintain clarity. This could potentially have biased respondents to select particular modalities. The replication of our US results in Study 1b (without definitions) indicates that participants’ judgments were not driven by the definitions, but we cannot rule this possibility out empirically for the other samples.

While intersubjectivity has many benefits, we also acknowledge possible downsides of this method. Even with the adjustments mentioned above, some caution needs be exercised when interpreting cultural differences, particularly due to variance between samples that may be explained by factors other than national culture. As we used a variety of approaches to collect data, our samples were not fully matched, and could potentially differ on characteristics such as socioeconomic status or religious orientation (see Cohen, 2009). Another key contributor to cultural differences is language (Kashima & Kashima, 1998). While we used an established method for translating all materials (team-translation approach: Clark et al., 2017), the possibility of language differences contributing to cultural differences on our measures cannot be ruled out.

Furthermore, this type of measure taps into peoples’ shared understanding of others’ expressions, which means that our results could reflect consensually shared stereotypes rather than actually occurring expressions. Stereotypes about emotional reactions are likely to reflect, at least in part, participants’ everyday observations. The fact that our results were largely consistent across 11 very different samples thus points to possible similarities in actually occurring behaviors. Another limitation of our measure is the level of granularity that our items tap into. For example, while ‘touch’ was provided as a modality option, our research tool was unable to differentiate between different forms of touch. In reality, a pat on the shoulder is of course hugely different from a slap in the face. Future work may refine the present tool to provide greater detail for each modality, perhaps with branch logic such that finer granularity is achieved within each option.

In a related vein, we recommend several lines of future research that could unpack why and how cultural differences manifest in the expression of positive emotions. We here point to two culture specific patterns we observed in our Chinese sample. First, Chinese participants overall selected fewer modalities in comparison to other countries, and second, we found culture specific patterns for expressions of feeling moved and gratitude. A possible explanation for the above findings could be cultural display rules, where some positive emotions are deemed less acceptable to express as compared to others (see Manokara et al., 2021). Future research could focus on cross-cultural comparisons, by blending classic production methods with the intersubjective approach, to understand whether the patterns we find reflect genuine cultural differences in emotion expressions, or mere differences in cultural representations.

Another extension for future work would be to examine the role of context in shaping emotion expressions. Incorporating features of the situation has been put forth as a recommendation for classic production studies as well (Greenaway et al., 2018), and researchers could start by empirically testing whether contextual information shapes self-reported emotion expressions, before investing greater resources in lab studies. We provide a tool that is flexible enough to allow for modification (see OSF for translated materials), as a first step in examining novel research questions.