Emoji as Affective Symbols: Affective Judgments of Emoji, Emoticons, and Human Faces Varying in Emotional Content

Affective, semantic, frequency, and descriptive norms for 107 face emojis

We introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties.

Is there an intergenerational discrepancy in the comprehension and aesthetic preference regarding emoji usage? Evidence from WeChat

Emojis are widely used on social media, blogs, and instant messaging to express users' feelings. However, in everyday interactions, the same emoji often has different interpretations and aesthetic preferences among different age groups. This can lead to communication barriers and misunderstandings. Based on social identity theory, this study uses WeChat, a social platform popular in China, to analyze intergenerational differences in emoji understanding and preferences through a questionnaire survey. The results indicate: (1) There are significant intergenerational differences in the usage habits, interpretation, and aesthetic preferences of emojis. (2) Middle-aged and elderly tend to interpret goodbye emoji symbols as simple emotional expressions, such as "goodbye" or "see you later," while younger-age groups lean towards more complex emotions and social intentions, such as "speechlessness" and "end of friendship." (3) Younger-age groups use emojis frequently and with a wide variety, whereas middle-aged and elderly groups use emojis less frequently and with limited variety. Younger individuals' aesthetic preferences for emojis lean towards humor, conflict, and narrative, whereas middle-aged and elderly groups prefer emojis with bright colors and everyday greetings typical of their generation. Based on research findings, we believe that social identity theory provides a framework for understanding how individuals establish their identities through interactions with specific social groups. This study is beneficial for identifying the comprehension and aesthetic biases in emoji usage across generations, sheds light on the broader implications of social identity theory in digital communication contexts, and promotes friendly social interactions in real-time communication applications.

Linking repeated subjective judgments and ConvNets for multimodal assessment of the immediate living environment

The integration of alternative data extraction approaches for multimodal data, can significantly reduce modeling difficulties for the automatic location assessment. We develop a method for assessing the quality of the immediate living environment by incorporating human judgments as ground truth into a neural network for generating new synthetic data and testing the effects in surrogate hedonic models. We expect that the quality of the data will be less biased if the annotation is performed by multiple independent persons applying repeated trials which should reduce the overall error variance and lead to more robust results. Experimental results show that linking repeated subjective judgements and Deep Learning can reliably determine the quality scores and thus expand the range of information for the quality assessment. The presented method is not computationally intensive, can be performed repetitively and can also be easily adapted to machine learning approaches in a broader sense or be transferred to other use cases. Following aspects are essential for the implementation of the method:•Sufficient amount of representative data for human assessment.•Repeated assessment trials by individuals.•Confident derivation of the effect of human judgments on property price as an approbation for further generation of synthetic data.

Gestures vs. Emojis: Comparing Non-Verbal Reaction Visualizations for Immersive Collaboration

Collaborative virtual environments afford new capabilities in telepresence applications, allowing participants to co-inhabit an environment to interact while being embodied via avatars. However, shared content within these environments often takes away the attention of collaborators from observing the non-verbal cues conveyed by their peers, resulting in less effective communication. Exaggerated gestures, abstract visuals, as well as a combination of the two, have the potential to improve the effectiveness of communication within these environments in comparison to familiar, natural non-verbal visualizations. We designed and conducted a user study where we evaluated the impact of these different non-verbal visualizations on users' identification time, understanding, and perception. We found that exaggerated gestures generally perform better than non-exaggerated gestures, abstract visuals are an effective means to convey intentional reactions, and the combination of gestures with abstract visuals provides some benefits compared to their standalone counterparts.

A study of dynamic emoji emotional responses based on rhythms and motion effects

Dynamic emojis are a form of nonverbal communication used in social programs to express emotions during conversations. Studies have shown that different dynamic effects can influence users' emotional perceptions. Previous studies have focused on the emotional responses elicited by static emojis, while the emotional responses to dynamic emojis have not been thoroughly explored. In this study, we examined the impact of 128 different dynamic effects, categorized into emotional types (HAHV, LAHV, HALV, and LALV), on users' arousal and valence, and conducted semi-structured interviews to identify users' preferred dynamic effects. The results revealed significant and positive correlations between the arousal levels of all dynamic emojis and the effects of rhythms. However, the impact of rhythms on the valence of dynamic emojis varied depending on the emotion types of emojis. Specifically, the effects of motion on the valence of dynamic high-valence emojis were found to be significant, whereas they were not significant for dynamic low-valence emojis. Based on these findings, we recommend considering following factors in the design of dynamic emojis, including rhythms, motion effects, motion range, emotional metaphors, and the creation of contrast.

Emotion recognition of faces and emoji in individuals with moderate-severe traumatic brain injury

BACKGROUND

Facial emotion recognition deficits are common after moderate-severe traumatic brain injury (TBI) and linked to poor social outcomes. We examine whether emotion recognition deficits extend to facial expressions depicted by emoji.

METHODS

Fifty-one individuals with moderate-severe TBI (25 female) and fifty-one neurotypical peers (26 female) viewed photos of human faces and emoji. Participants selected the best-fitting label from a set of basic emotions (anger, disgust, fear, sadness, neutral, surprise, happy) or social emotions (embarrassed, remorseful, anxious, neutral, flirting, confident, proud).

RESULTS

We analyzed the likelihood of correctly labeling an emotion by group (neurotypical, TBI), stimulus condition (basic faces, basic emoji, social emoji), sex (female, male), and their interactions. Participants with TBI did not significantly differ from neurotypical peers in overall emotion labeling accuracy. Both groups had poorer labeling accuracy for emoji compared to faces. Participants with TBI (but not neurotypical peers) had poorer accuracy for labeling social emotions depicted by emoji compared to basic emotions depicted by emoji. There were no effects of participant sex.

DISCUSSION

Because emotion representation is more ambiguous in emoji than human faces, studying emoji use and perception in TBI is an important consideration for understanding functional communication and social participation after brain injury.

Emoji-SP, the Spanish emoji database: Visual complexity, familiarity, frequency of use, clarity, and emotional valence and arousal norms for 1031 emojis

This article presents subjective norms for 1031 emojis in six dimensions: visual complexity, familiarity, frequency of use, clarity, emotional valence, and emotional arousal. This is the largest normative study conducted so far that relies on subjective ratings. Unlike the few existing normative studies, which mainly comprise face emojis, here we present a wide range of emoji categories. We also examine the correlations between the dimensions assessed. Our results show that, in terms of their affective properties, emojis are analogous to other stimuli, such as words, showing the expected U-shaped relationship between valence and arousal. The relationship between affective properties and other dimensions (e.g., between valence and familiarity) is also similar to the relationship observed in words, in the sense that positively valenced emojis are more familiar than negative ones. These findings suggest that emojis are suitable stimuli for studying affective processing. Emoji-SP will be highly valuable for researchers of various fields interested in emojis, including computer science, communication, linguistics, and psychology. The full set of norms is available at: https://osf.io/dtfjv/ .

Emojis Are Comprehended Better than Facial Expressions, by Male Participants

Emojis are colorful ideograms resembling stylized faces commonly used for expressing emotions in instant messaging, on social network sites, and in email communication. Notwithstanding their increasing and pervasive use in electronic communication, they are not much investigated in terms of their psychological properties and communicative efficacy. Here, we presented 112 different human facial expressions and emojis (expressing neutrality, happiness, surprise, sadness, anger, fear, and disgust) to a group of 96 female and male university students engaged in the recognition of their emotional meaning. Analyses of variance showed that male participants were significantly better than female participants at recognizing emojis (especially negative ones) while the latter were better than male participants at recognizing human facial expressions. Quite interestingly, male participants were better at recognizing emojis than human facial expressions per se. These findings are in line with more recent evidence suggesting that male individuals may be more competent and inclined to use emojis to express their emotions in messaging (especially sarcasm, teasing, and love) than previously thought. Finally, the data indicate that emojis are less ambiguous than facial expressions (except for neutral and surprise emotions), possibly because of the limited number of fine-grained details and the lack of morphological features conveying facial identity.

Are you really smiling? Display rules for emojis and the relationship between emotion management and psychological well-being

Display rules specify socially appropriate facial expressions in a given situation. However, managing emotions for such a social adaption sometimes leads to deleterious psychological outcomes. Given that people nowadays rely on emojis to express emotions online, the present study investigated (1) whether display rules exist in emoji communications and (2) how emotion management using emojis is associated with psychological well-being. Prior studies have demonstrated the effects of context on the frequency of emoji use. However, the intensity and type of expression may differ, even if emojis are used at the same frequency. The current study thus investigated whether emotional expressions and the types of emojis used are adjusted to contexts similar to facial displays. As many as 1,289 Japanese participants typed emojis in response to Internet chats and reported the intensity of their emotional expressions. The contexts of the chats varied depending on the target of use, the emotional value of contexts, and private or public settings. The results showed that, similar to facial displays, individuals expressed emotions through emojis more with those closely related, more in positive contexts than in negative contexts, and more in private than in public contexts. When the expressions were intense, individuals used emojis consistent with the emotional value of the context. Upon attenuating the expressions, this study found that individuals tended to use euphemistic emojis and sent smiling emojis in negative contexts to manage the expressions. Moreover, expressing emotions with emojis was associated with subjective well-being, whereas managing emotions with emojis was weakly associated with depressive symptoms. Together, this study indicates the existence of display rules for emojis, calling for future research on the psychological impact of online emotion norms.

Using Emoji in Response to Customer Reservation Requests and Service Reviews

The use of paralinguistic cues—including emoji—in computer-mediated communication has become prevalent in recent years. Brands and service providers have also been using these cues in their communication strategies. And yet, research examining how such emoji use influences customers’ perception and behavior is still scarce. In two experiments (combined $N=401$ ), we tested if using emoji to reply to a customer request (restaurant reservation, Study 1) or online review (hotel experience, Study 2) influenced perceptions of the brands. The emoji used by the brand was always congruent with the valence of the situation. Results from both studies revealed that the presence (vs. absence) of emoji influenced consumers’ perception of the brand/service at several levels. Specifically, the restaurant/hotel was perceived to have a more informal communication style, have a warmer service, and be more modern. In Study 1, we also observed that emoji use had a positive impact on competence perception and reservation intentions. Importantly, these effects of emoji use were not moderated by the valence of the situation. Taken together, our results showed that emoji can influence different perceptions about brands and services and determine how customers relate to brands.

Influence of Emojis on Online Trust Among College Students

Emojis are increasingly used in online communication and expression, however, most previous studies have focused on describing this phenomenon, but less on how it affects interpersonal trust relationships. Therefore, this study examines the effect of emojis on online interpersonal trust among college students through three experiments. A total of 62 college students were recruited for Experiment 1. The results demonstrated that positive emoji () improved the level of trust of trustors in the trust game [t(60) = –2.79, p = 0.007], whereas that of the control group exerted no effect on the initial level of online trust among college students. Then, 74 college students were selected for Experiment 2. The results indicated no significant differences between the experiment and control groups in terms of the influence of negative emojis () on initial online trust using. A joint analysis (via ANOVA) of Experiments 1 and 2 illustrated that the type of emoji exerted a significant effect [F(2,96) = 3.96, p = 0.02, η² = 0.08] on college students’ online trust. Finally, we recruited 111 participants for Experiment 3 to explore the role of emojis on online trust among acquaintances. The results suggested that the individual propensity to trust plays a moderate role in the relationship between emojis and online trust among acquaintances. That is, emojis influenced interpersonal trust among acquaintances only if the level of propensity to trust, is low.