{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232966","sets":["1164:11259:11454:11518"]},"path":["11518"],"owner":"44499","recid":"232966","title":["動画共有サイト利用者に推薦動画偏向現象の気づきを与える動画感情推定・可視化手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-04"},"_buckets":{"deposit":"e43d020e-dbda-460d-80e5-4ee99a57861b"},"_deposit":{"id":"232966","pid":{"type":"depid","value":"232966","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"動画共有サイト利用者に推薦動画偏向現象の気づきを与える動画感情推定・可視化手法","author_link":["631722","631724","631723","631721"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"動画共有サイト利用者に推薦動画偏向現象の気づきを与える動画感情推定・可視化手法"},{"subitem_title":"Proposal and Evaluation of a Video Sentiment Estimation and Visualization Method to Make Users of Video Sharing Websites Aware of the Recommendation Video Bias","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"アウェアネス，集合知","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-03-04","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"和歌山大学大学院システム工学研究科"},{"subitem_text_value":"和歌山大学システム工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Systems Engineering, Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Systems Engineering, Wakayama University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/232966/files/IPSJ-CN24122004.pdf","label":"IPSJ-CN24122004.pdf"},"date":[{"dateType":"Available","dateValue":"2026-03-04"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CN24122004.pdf","filesize":[{"value":"945.8 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"29"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"eea76e10-a70a-4a36-89a9-62a62f36b379","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"米田, 優斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"塚田, 晃司"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuto, Yoneda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Koji, Tsukada","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_relation_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_select":"NCID","subitem_relation_type_id_text":"AB00006906"}}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2758-8262","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，ソーシャルメディア上で起こるフィルターバブルが問題視されている．そこで本研究では，YouTube 上で推薦される動画の感情を推定し，推薦される動画の感情面の傾向を可視化するシステムを提案する．本提案システムを用いることで，YouTube 上で起こる推薦動画の偏向現象の気づきを与え，フィルターバブルを認識・判断する機会を与えることを目指した．本研究では，推定精度・フィルターバブルに対する有効性について機械学習の評価指標やアンケート調査にて評価を行った．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, the filter bubble that occurs in social media has become an issue. To address this problem, we propose a system that estimates the sentiment of videos recommended on YouTube and visualizes the emotional trends of recommended videos. By using the proposed system, we aim to make the user aware of the deflection phenomenon of recommended videos on YouTube, and to give the user the opportunity to recognize and judge the filter bubble. In this study, we evaluate the estimation accuracy and effectiveness of the system against the filter bubble using machine learning metrics and a questionnaire survey.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コラボレーションとネットワークサービス（CN）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2024-CN-122"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232966,"updated":"2025-01-19T10:15:38.452831+00:00","links":{},"created":"2025-01-19T01:34:08.227353+00:00"}