{"created":"2024-10-29T00:24:32.824823+00:00","id":2006361,"links":{},"metadata":{"_buckets":{"deposit":"8ef921b6-9820-4010-a270-04b70fb5004f"},"_deposit":{"created_by":7,"id":"2006361","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2006361"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02006361","sets":["1713853213384:1713853295607"]},"author_link":["311","641","94"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"133","bibliographicPageStart":"121","bibliographicVolumeNumber":"10","bibliographic_titles":[{"bibliographic_title":"International Journal of Advanced Intelligence","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this study, we focus on Twitter as a representative SNS and target emotion estimation from tweets posted on Twitter by male and female users. Specifically, we construct gender-based emotion estimation models assuming that there are different word usage tendencies between genders. By analyzing gender-specific differences in the use of emotion-related slang and emoji, we propose a method to improve emotion estimation based on neural networks using a different distributed representation model for each gender. Our evaluation experiments show that training with Deep Convolutional Neural Networks using word's distributed representation as the feature produced higher estimation accuracy than training with Feed Forward Neural Networks.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"AIA International Advanced Information Institute","subitem_publisher_language":"en"}]},"item_10001_source_id_9":{"attribute_name":"収録物ID","attribute_value_mlt":[{"subitem_source_identifier":"18833918","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access"}]},"item_1723180141928":{"attribute_name":"EID","attribute_value_mlt":[{"subitem_identifier_type":"URI","subitem_identifier_uri":"350088"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"フジノ, ナオヤ","creatorNameLang":"ja"},{"creatorName":"フジノ, ナオヤ","creatorNameLang":"ja-Kana"},{"creatorName":"Fujino, Naoya","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"松本, 和幸","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"311","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"吉田, 稔","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"641","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"北, 研二","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"94","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-05-13"}],"displaytype":"detail","filename":"ijai_10_1_121.pdf","filesize":[{"value":"449 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://tokushima-u.repo.nii.ac.jp/record/2006361/files/ijai_10_1_121.pdf"},"version_id":"1698e238-d512-4055-8f94-c6c50d62d9c4"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"emotion estimation","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"user's gender","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"deep neural networks","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Emotion Estimation Adapted to Gender of User Based on Deep Neural Networks","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Emotion Estimation Adapted to Gender of User Based on Deep Neural Networks","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"7","path":["1713853295607"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2019-05-13"},"publish_date":"2019-05-13","publish_status":"0","recid":"2006361","relation_version_is_last":true,"title":["Emotion Estimation Adapted to Gender of User Based on Deep Neural Networks"],"weko_creator_id":"7","weko_shared_id":-1},"updated":"2024-10-29T00:24:41.020043+00:00"}