Facial expressions of emotion are nonverbal cues that evoke affective, inferential, and social responses during face-to-face communication. Given that communication is moving more and more from face-to-face to digital contexts, the present research tested the functional equivalence of their digital counterparts—emojis. Eleven high-powered experiments tested the general effectiveness of emojis to convey emotionality and to disambiguate discourse during digital communication, as well as predictions about their social-emotional properties derived from the Emotion as Social Information (EASI) model. Compared to messages without emojis, those including emojis were perceived as emotionally more intense and as of more extreme valence. Furthermore, the effects of emojis on perceived valence were mediated via perceived emotional intensity. This suggests that emojis are effective quasi-nonverbal cues for digital communication. Furthermore, in line with predictions of the EASI model, emojis produced patterns similar to what has been observed for facial expressions of emotion in face-to-face communication, supporting their functional equivalence. Specifically, they instigated affective (emotion contagion) and inferential (understanding) processes, which subsequently resulted in behavioral intentions (empathic concern). In terms of the predicted mediating processes, we found differences between emojis and offline facial expressions of emotion. These deviations from our predictions are attributed to inherent differences between digital and face-to-face communication and limitations in the employed methodology. In light of the present findings, we discuss a theoretical synthesis of emojis in digital communication with the EASI model and propose a research agenda to connect emotion research with predominant forms of modern communication.