Abstract
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 are 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 a 15-day longitudinal field deployment with 18 participants. We found that participants picked more semantic suggestions than lexical suggestions and perceived the semantic suggestions as more relevant to the message content. Our subjective data showed that although the suggestion mechanism did not affect the chatting experience significantly, different mechanisms could change the composing behavior of the users and facilitate their emoji-searching needs in different ways.
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This work was supported in part by Baidu Inc. Any opinions, findings, conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect those of any supporter.
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Zhang, M.“., Mariakakis, A., Burke, J., Wobbrock, J.O. (2021). A Comparative Study of Lexical and Semantic Emoji Suggestion Systems. In: Toeppe, K., Yan, H., Chu, S.K.W. (eds) Diversity, Divergence, Dialogue. iConference 2021. Lecture Notes in Computer Science(), vol 12645. Springer, Cham. https://doi.org/10.1007/978-3-030-71292-1_20
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