Emoticon Recommendation System to Richen Your Online Communication
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 contai...
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| Veröffentlicht in: | International journal of multimedia data engineering & management 2014-01, Vol.5 (1), p.14-33 |
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| container_title | International journal of multimedia data engineering & management |
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| creator | Urabe, Yuki Rzepka, Rafal Araki, Kenji |
| description | 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. |
| doi_str_mv | 10.4018/ijmdem.2014010102 |
| format | Article |
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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.</description><identifier>ISSN: 1947-8534</identifier><identifier>EISSN: 1947-8542</identifier><identifier>DOI: 10.4018/ijmdem.2014010102</identifier><language>eng</language><publisher>Hershey: IGI Global</publisher><subject>Analysis ; Computer mediated communication ; Emotional icons ; Emotions ; Filtering systems ; Instant messaging ; Recommender systems ; Smart phones ; Smartphones ; Social networks</subject><ispartof>International journal of multimedia data engineering & management, 2014-01, Vol.5 (1), p.14-33</ispartof><rights>COPYRIGHT 2014 IGI Global</rights><rights>Copyright © 2014, IGI Global. 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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.</description><subject>Analysis</subject><subject>Computer mediated communication</subject><subject>Emotional icons</subject><subject>Emotions</subject><subject>Filtering systems</subject><subject>Instant messaging</subject><subject>Recommender systems</subject><subject>Smart phones</subject><subject>Smartphones</subject><subject>Social networks</subject><issn>1947-8534</issn><issn>1947-8542</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kV1LwzAUhoMoOOZ-gHcFbxTszFeT9nKOOYXBYO7Gq9BlaZfRNrNpL_bvPVvF4dAEck7gOW_enIPQLcFDjkn8ZLfl2pRDiglcYdML1CMJl2EccXr5kzN-jQbebzGsiEtJeA89T0rXWO2qYGG0K0tTrdPGwvV97xtTBo0LFlZvTBV8uLYO5lVhKxOMgWwrq4_oDbrK0sKbwXfso-XLZDl-DWfz6dt4NAt1RHkTaqoZjeDlLKaGyJXmMsloKknKmMREMMmwJliwTHMjTSwpJwJMygjSlWB9dN_J7mr32RrfqNJ6bYoirYxrvSJCYEyIjGNA787QLZivwJyiCaNMJjHEPnrsqDwtjFq1Hn7m4fA23zQ-T1vv1UgKHMlIxAxw0uG6dt7XJlO72pZpvVcEq8MYVDcGdRoD1Ey7Gpvbk4dDu9Xvdqtju_8VikDp4S-lc1Dt1hn7Ai0Wn3c</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Urabe, Yuki</creator><creator>Rzepka, Rafal</creator><creator>Araki, Kenji</creator><general>IGI Global</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>7SC</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>8BP</scope><scope>E3H</scope><scope>F2A</scope></search><sort><creationdate>20140101</creationdate><title>Emoticon Recommendation System to Richen Your Online Communication</title><author>Urabe, Yuki ; 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| fulltext | fulltext |
| identifier | ISSN: 1947-8534 |
| ispartof | International journal of multimedia data engineering & management, 2014-01, Vol.5 (1), p.14-33 |
| issn | 1947-8534 1947-8542 |
| language | eng |
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| source | ProQuest Central UK/Ireland; Alma/SFX Local Collection; ProQuest Central |
| subjects | Analysis Computer mediated communication Emotional icons Emotions Filtering systems Instant messaging Recommender systems Smart phones Smartphones Social networks |
| title | Emoticon Recommendation System to Richen Your Online Communication |
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