This study aimed to assess how various facial emojis are classified in the valence and arousal axes, and to examine the relationship between these emojis and the human emotional states using the core affect theory. Based on the data of 1,082 participants, we analyzed the valence and arousal levels indicated by each of the 74 emojis. The emojis used in this experiment tended to be distributed in a U-shape on the two axes (Fig. 1), which was similar to a previous study’s result that employed only 33 facial emojis5. The present research’s emojis were classified into six different clusters on the two axes, as we hypothesized initially. Further, these clusters had six valence and three arousal levels (Table 1). Thus, each cluster was interpreted as: (1) a strong negative sentiment, (2) a moderately negative sentiment, (3) a neutral sentiment with a negative bias, (4) a neutral sentiment with a positive bias, (5) a moderately positive sentiment, and (6) a strong positive sentiment. A previous study categorized emojis into only three levels on the valence axis, possibly because it utilized limited emojis and focused only on one axis constituting the human emotional states. However, the present study confirmed that the emojis could be classified into six clusters on the valence and arousal axes by using plenty of them and that both axes constituted the human emotional state. Therefore, it was concluded that emojis could display the human emotional states in a greater detail than that reported previously.
The human emotional states (the core affect) are circularly aligned on the valence and arousal axes 4. Because this study acquired the valence and arousal levels indicated by each emoji, all six clusters could be corresponded with the emotional states described in the core affect (Fig. 2), which has been discussed in the following sections.
In the “strong negative sentiment” cluster, the following 12 emojis were classified: 😠, 😡, 🤬, 😫, 😩, 😤, 😱, 😰, 😭, 🤢, 🥵, 🥶. This cluster was characterized by extremely low valence and high arousal levels (valence: 2.74 ± 0.40, arousal: 6.91 ± 0.37). The human emotional states based on the core affect4 that are considered to correspond with such levels would be "Nervous,” “Stressed,” and “Upset.” In present study, emojis named “Confounded face 😖,” “Tired face 😫” and “Angry face 😠” were classified into this cluster. These emojis have also been categorized in the “negative sentiment” cluster, interpreted with the words “Nervous / anxious / worried”, “Stressed”, and “Angry / annoyed,” in previous study5. However, a prior research included the emoji named “face screaming in fear 😱” in the “neutral/dispersed sentiment” cluster. Additionally, it may be interesting to note that this cluster did not have an emoji with the corners of the mouth raised (i.e., smiling). These results indicated that the emojis classified in this cluster corresponded appropriately to the emotional state of the core affect in general; however, some emojis’ interpretations require caution because they are inconsistent across studies.
In the “moderately negative sentiment” cluster, the following 10 emojis were classified: 😒, 😟, 😔, 😣, 😖, 😨, 😢, 😥, 😵, 🤯. Its characteristics were low valence and moderate arousal levels (valence: 3.59 ± 0.37, arousal: 5.84 ± 0.30). The human emotional states that were considered to correspond with these levels were “sad” and "depressed.” The present study evidently classified the emojis named “crying face 😢” and “Pensive face 😔” in this cluster. These emojis have also been categorized in the “negative sentiment” cluster, and both of them interpreted with the words “Sad / unhappy” and “depressed,” in previous study5. Furthermore, none of this cluster’s emojis were grouped into the more positive clusters (i.e. “neutral/dispersed sentiment” and “positive sentiment”) in previous research. Additionally, this cluster did not include the emojis with a raised corner of the mouth (i.e., smiling), similar to those classified into the “strong negative sentiment” cluster. Therefore, it was reasonable to infer that the emojis grouped into this cluster corresponded exceedingly well to the emotional state of the core affect.
In the “neutral sentiment with a negative bias” cluster, the following 19 emojis were included: 😅, 😶, 😐, 😑, 🙄, 🤨, 😞, 😕, 🙁, ☹, 😬, 🥺, 😯, 😦,😧, 😪, 😓, 🥴, 😗. Its characteristics were a low to moderate valence and a low arousal level (valence: 4.27 ± 0.38, arousal: 4.83 ± 0.27). The human emotional states that were considered to resemble these levels were “lethargic” and “fatigue.” The emojis named “expressionless face 😑,” “neutral face 😐,” and “grimacing face 😬” were grouped into this cluster; they were also categorized in the “neutral/dispersed sentiment” cluster. In a previous research, the former two emojis were interpreted using the words “neutral/indifferent,” “no comments/opinion,” and “confused/unsure” and were considered to be close to the emotional states represented by this cluster. However, the interpretation of the “grimacing face 😬” emoji in a previous study included both positive (i.e. “happy” and “excited”) and negative emotions (i.e. “nervous/anxious,” “worried,” and “stressed”). Therefore, it was rational to infer that the emojis classified in this cluster corresponded appropriately to the emotional state of the core affect in general; however, some emojis require caution because their interpretations can vary.
In the “neutral sentiment with a positive bias” cluster, the following 12 emojis were classified: 🙂, 😌, 😛, 😎, 🧐, 🤠, 🤡, 🤔, 🤭, 😳, 😮, 😲. Its characteristics comprised a moderate to high valence and a low arousal level (valence: 5.49 ± 0.38, arousal: 5.19 ± 0.29). The human emotional states that were considered to correspond with these levels were “calm,” “relaxed,” and “serene.” The “relieved face 😌” emoji was classified in this cluster. However, none of the emojis grouped into this cluster in this study were categorized into the “neutral/dispersed sentiment” cluster in a previous one. The “smiling face with sunglasses 😎,” “relieved face 😌,” and “face with tongue 😛” emojis were grouped into the “positive sentiment” cluster; additionally, the previous study’s participants interpreted them using the words “be/act cool,” “happy,” “naughty/playful,” “exited,” and “content/satisfied.” Hence, it can be considered that this cluster’s emojis represented a slightly greater positive emotional state than the valence and arousal levels.
In the “moderately positive sentiment” cluster, the following 9 emojis were classified: 😀, 😃, 😇, 😉, 😋, 😙, 😜, 😝, 🤗. Its characteristics were high valence and moderate arousal levels (valence: 6.57 ± 0.62, arousal: 5.98 ± 0.29). The human emotional states that were considered to resemble with these levels were “contented” and “happy.” Interestingly, all emojis in this cluster had a raised corner of the mouth or smiling eyes (i.e., they were smiling). None of them were classified into the more negative clusters (i.e. “neutral/dispersed sentiment” and “negative sentiment”) in previous studies. Therefore, this cluster’s emojis corresponded well with the emotional states in the core affect.
In the “strong positive sentiment” cluster, the following 12 emojis were categorized: 😄, 😁, 😆, 🤣, ☺, 😊, 😍, 🥰, 😘, 😚, 🥳, 🤩. The human emotional states that were considered to correspond to these levels were “elated” and “excited.” All emojis in this cluster had a raised corner of the mouth or smiling eyes (i.e., they were smiling), similar to the those classified into the “moderately positive sentiment” cluster. Additionally, many of them indicated richer expressions, such as heart (star)-shaped eyes, pink cheeks, or throwing hearts. The “smiling face with smiling eyes 😊” emoji was interpreted using the words “happy,” “feeling good,” and “excited” in present study5. Further, similar to the “moderately positive sentiment” cluster, none of the emojis classified into this one in the present study were grouped into the more negative clusters (i.e. “neutral/dispersed sentiment” and “negative sentiment”) in previous research. Therefore, it was acceptable to deduce that the emojis classified into this cluster corresponded extremely well to the emotional state of the core affect.
The emojis used in this experiment and a previous study5 were distributed in a U-shape on the two axes of valence and arousal, while the human emotional states (the core affect) were circularly aligned on these axes 4. Therefore, emojis at least used in present and previous study may not be able to capture the human emotional states with neutral valence and high arousal level (i.e., “tense” and “alert”). Jaeger et al.5 noted that "open-mouthed facial emoticons (e.g., 😲, 😧)," which indicate surprise expressions, may indicate a higher level of arousal. In fact, arousal level for these emojis in present study was somewhat higher than the mean of clusters 4 in which these emojis were included (5.52 and 5.24 respectively, while the mean for cluster 4 was 5.19). However, these emojis could not reach sufficient levels of arousal to capture “tense” and “alert”. Because current and previous study used major facial emojis, it may be difficult to indicate these emotional states by current set of emojis. We encourage the emoji designers to produce new emojis that can express these human emotional states.
The fact that emojis can display the human emotional states in a considerably greater detail than reported previously will accelerate their use in research fields such as consumer studies that need to evaluate these states. This is because the traditional text-based methods taxing for the participants9, and emojis are considered an easier way to examine the human emotional states. In addition, the latter may have the advantage of being less sensitive to the participants' native language than the former. However, this study, as well as the other ones on the human emotional states expressed by emojis, have many limitations, which are discussed in the following section. Further research is warranted to deepen our understanding of the relationship between emojis and human emotional states; nevertheless, this would further increase the emoji use in various research areas where the human emotional states need to be assessed.
This study has several limitations that must be acknowledged when interpreting the results. Firstly, all the participants of this study were young Japanese adults and individuals with other demographics were not included (i.e., age, sex, and culture). Although the “use” of emojis has been reported to be significantly influenced by demographic characteristics such as age, gender, and culture2, their “interpretation” has been indicated NOT to be significantly impacted by these characteristics5,10,11. Therefore, we believe that the results of this study are consistent with other demographics.
Secondly, we cannot deny the possibility that slight differences in the emoji design may have affected this research’s findings because we only employed the emojis displayed on the twitter. Even with the same code, the emoji designs displayed on different devices, such as PC, mac, Android, and iPhone, vary slightly. Since researches using emoji are conducted with various types of devices, it may be necessary to understand how minor discrepancies in the emoji designs displayed on different types of devices affect the interpretation of the human emotional states.
Finally, we associated emojis with the human emotional states INDIRECTLY based on the valence and arousal axes and the theory of core affect4. This is because the primary purpose of this study was to understand how various facial emojis are classified on these axes. Further research is warranted to directly relate the human emotional states with emojis. However, we believe that the results of this study are sufficiently reliable because the interpretation of emojis in each cluster was consistent with that reported by a previous study, which directly linked the human emotional states with emojis using open-ended questions.
This study purported to understand how various facial emojis are categorized on the valence and arousal axes, and to assess the relationship between these emojis and the human emotional states. It provided evidence that the emojis could be grouped into the following six clusters on the two axes of valence and arousal: (1) a strong negative sentiment, (2) a moderately negative sentiment, (3) a neutral sentiment with a negative bias, (4) a neutral sentiment with a positive bias, (5) a moderately positive sentiment, and (6) a strong positive sentiment. Further, we corresponded each of these clusters with the emotional states described in the core affect theory. Thus, we concluded that the emojis display the human emotional states in a considerably greater detail than that reported previously. This would accelerate their use in research fields that need to evaluate the human emotional states.