{"updated":"2025-01-19T10:41:24.831279+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231611","sets":["1164:3027:11450:11451"]},"path":["11451"],"owner":"44499","recid":"231611","title":["回帰分析による推薦システムの性能に対する知覚と推薦受容傾向の関係の理解"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-01-08"},"_buckets":{"deposit":"4734a667-2eea-434b-9ee8-56c21fa5267d"},"_deposit":{"id":"231611","pid":{"type":"depid","value":"231611","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"回帰分析による推薦システムの性能に対する知覚と推薦受容傾向の関係の理解","author_link":["625539","625537","625538","625541","625540"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"回帰分析による推薦システムの性能に対する知覚と推薦受容傾向の関係の理解"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"推薦・誘発","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-01-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"関西学院大学"},{"subitem_text_value":"関西学院大学"},{"subitem_text_value":"産業技術総合研究所"},{"subitem_text_value":"産業技術総合研究所"},{"subitem_text_value":"関西学院大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kwansei Gakuin University","subitem_text_language":"en"},{"subitem_text_value":"Kwansei Gakuin University","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"Kwansei Gakuin 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/231611/files/IPSJ-HCI24206010.pdf","label":"IPSJ-HCI24206010.pdf"},"date":[{"dateType":"Available","dateValue":"2026-01-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-HCI24206010.pdf","filesize":[{"value":"1.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"33"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"73bc9166-8aaf-4c57-b020-8139f39519bd","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":"木村, 有那"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"井野, 泰輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"濱崎, 雅弘"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"後藤, 真孝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"土方, 嘉徳"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA1221543X","subitem_source_identifier_type":"NCID"}]},"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":"2188-8760","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"人工知能による推薦や判断を導入したサービスが普及するとともに，ユーザは提示された記事やコンテンツを吟味することなく消費する「推薦過信」の問題がおきつつある．我々は，推薦過信に陥っていないかどうかを知るための参考となる心理尺度として，推薦結果を受け入れやすい傾向にあるかどうかを測定する推薦受容傾向尺度を開発してきた．本稿では，従来から推薦システムのユーザ評価で用いられてきた推薦性能に対する知覚評価から，推薦受容傾向尺度の値を予測できるかどうかを大規模社会調査により明らかにする．YouTube と TikTok における推薦機能を対象にした社会調査をクラウドソーシングサービス上で別々に実施し，それぞれ 1298 人の回答を得た．これらの回答を重回帰分析により分析したところ，推薦受容傾向は，推薦システムに対する能力と親切性，透明性により予測できることがわかった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告ヒューマンコンピュータインタラクション（HCI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-01-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"10","bibliographicVolumeNumber":"2024-HCI-206"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:32:00.937655+00:00","id":231611,"links":{}}