Emoji suggestion systems based on typed text have been proposed to encourage emoji usage and enrich text messaging; however, such systems’ actual effects on the chat experience remain unknown. We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared these in two different studies. To investigate the effect of emoji suggestion in online conversations, we conducted a laboratory text-messaging study with 24 participants, and also a 15-day longitudinal field deployment with 18 participants. We found that lexical emoji suggestions increased emoji usage by 31.5% over a keyboard without suggestions, while semantic suggestions increased emoji usage by 125.1%. However, suggestion mechanisms did not affect the chatting experience significantly. From these studies, we formulate a set of design guidelines for future emoji suggestion systems that better support users’ needs. Based on the analysis of emoji counts in the study, we found that although different suggestion levels resulted in similar amounts of inputted emoji, participants tended to pick more from semantic suggestions than from lexical suggestions. One surprising finding was that although the usage of emojis indeed affected the senders' chat experience, the suggestion type did not affect the chat experience significantly. One explanation is that different suggestion mechanisms only affect how the user inputs emojis, rather than what they input. As long as they can input the expected emojis, the chat experience is not affected. Looking at participants' interview answers, we found that participants did notice the difference between the suggestion mechanisms, and provided more positive feedback on semantic suggestions than the other conditions. Five participants mentioned that semantic suggestions were convenient and timesaving. The convenience might come from the relevance of the semantic suggestions. P13 pointed out, "The first one [semantic] is better than the second one [lexical] , showing more emotion-related emojis. The second one is related to the word itself and it makes no sense to use the emoji in the conversation." Although P19 did not use many emojis during the study, she stated that "their [emojis'] appearance in suggestion bars makes me feel good." This feedback supports our finding that people chose more emojis from semantic suggestion than lexical suggestion. The quantitative analysis results are similar to the in-lab study: the total emoji inputs were similar between different suggestion levels in period 2, and users chose more semantic suggestions than lexical suggestions. Again, based on the survey results, suggestion mechanisms did not influence the online conversation experience significantly. [2, 9] , and also provides supporting evidence of why people picked more semantic emojis in our online study. Our goal was to examine the impact of emoji suggestion on online conversations. In particular, we sought to answer two primary questions: (1) How do emoji suggestion systems affect the chat experience? (2) Do lexical and semantic suggestion systems affect daily emoji usage differently? We first conducted an online study to evaluate the performance of the two systems, finding that semantic emoji suggestions were perceived as more relevant than lexical emoji suggestions. We then conducted two experiments, finding that emoji usage had a stronger effect on senders than on receivers, but the suggestion system in use did not affect the overall chat experience. A possible explanation is that the suggestion levels only affect the ease of inputting an emoji. Although participants picked more from the semantic suggestions, they could still manually pick their desired emojis if those emojis were not suggested, leading to similar numbers of total emojis inputted with the different suggestion systems. However, both our in-lab study and our field deployment revealed that the suggestion systems influenced how users reflected on their own experiences. Participants were clearly most excited about semantic suggestions. Even without knowing the details of the different suggestion systems, the participants were pleasantly surprised that the predicted emojis were related to the sentiment of their messages. During the field deployment, participants used more emojis in their daily conversations from semantic suggestions than from lexical suggestions. This finding shows that the semantic suggestions provided more relevant emojis than did the lexical suggestions. In this work, we compared two emoji suggestion systems: lexical and semantic. Specifically, we explored whether the suggestion type affected the online chat experience and how people perceive the two suggestion types. Our online crowdsourced study revealed that people perceived semantic suggestions as most relevant. Our laboratory study showed that semantic emoji suggestions were used about 1.5 times more than lexical emoji suggestions. Our longitudinal field deployment showed that semantic suggestions led to an increase in emoji usage and were preferred because of their relevance to emotions. As other research in this area has found [6, 11, 13] , we can conclude that emojis themselves, rather than the type of suggestion system, affects the chat experience most profoundly. Based on our study results, we offered design guidelines for emoji suggestion systems. We believe that by incorporating semantic information in emoji suggestion, researchers can provide better experiences in text-based computer-mediated communications.
We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared their effects in two different chat studies. 
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