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Emoticon Recommendation System to Richen Your Online Communication

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Title: Emoticon Recommendation System to Richen Your Online Communication
Authors: Urabe, Yuki Browse this author
Rzepka, Rafal Browse this author →KAKEN DB
Araki, Kenji Browse this author →KAKEN DB
Keywords: Affect Analysis
Application, Emoticon
Recommendation System
Issue Date: 2014
Publisher: IGI Global
Journal Title: International Journal of Multimedia Data Engineering and Management
Volume: 5
Issue: 1
Start Page: 14
End Page: 33
Publisher DOI: 10.4018/ijmdem.2014010102
Abstract: Japanese emoticons are widely used to express users' feelings and intentions in social media, blogs and instant messages. Japanese smartphone keypads have a feature that shows a list of emoticons, enabling users to insert emoticons simply by touching them. However, this list of emoticons contains more than 200, which is difficult to choose from, so a method to reorder the list and recommend appropriate emoticons to users is necessary. This paper proposes an emoticon recommendation method based on the emotive statements of users and their past selections of emoticons. The system is comprised of an affect analysis system and an original emoticon database: a table of 59 emoticons numerically categorized by 10 emotion types. The authors' experiments showed that 73.0% of chosen emoticons were among the top five recommended by the system, which is an improvement of 43.5% over the method used in current smartphones, which is based only on users' past emoticon selections.
Type: article (author version)
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: Rzepka, Rafal

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