Emoticon Recommendation for Japanese Computer-Mediated Communication

This paper describes the development of an emoticon recommendation system based on emoticons numerically categorized by emotion. The emoticon recommendation system aims to help users express their feelings in computer-mediated communication by recommending emoticons appropriate to user input. In order to develop this system, the original emoticon database, a table of emoticons with the points expressed from each of 10 distinctive emotions, was developed. An evaluation experiment showed that 71.3% of user-selected emoticons were among the top 10 emoticons recommended by the proposed system. Moreover, we compared the proposed system to the current system used in iPhone by adopting a semantic differential (SD) scale of 1-7. The results showed that the proposed system scored higher than the current system by 1.05 points in ease of choice, 0.55 points in accuracy, and 0.55 points in specificity. We plan to make our proposed method open source, so that any developer can build in their own interfaces and enhance their own input methods using these emoticon recommendation systems.