{"updated":"2025-02-17T04:57:18.686484+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02000313","sets":["1164:4842:1739765282477:1739765395873"]},"path":["1739765395873"],"owner":"80578","recid":"2000313","title":["テキスト生成AIによる自由記述のラベル付けの安定性：AIと著作権に関するパブコメ分析から"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-02-08"},"_buckets":{"deposit":"ee6e112c-c22a-47a6-9ccb-270446e3b8b9"},"_deposit":{"id":"2000313","pid":{"type":"depid","value":"2000313","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"テキスト生成AIによる自由記述のラベル付けの安定性：AIと著作権に関するパブコメ分析から","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"テキスト生成AIによる自由記述のラベル付けの安定性：AIと著作権に関するパブコメ分析から","subitem_title_language":"ja"},{"subitem_title":"Stability of Labeling Free-Text Responses with Text-Generative AI: Insights from Public Comments on AI and Copyright","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2025-02-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"広島大学"},{"subitem_text_value":"帝京大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hiroshima University","subitem_text_language":"en"},{"subitem_text_value":"Teikyo 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/2000313/files/IPSJ-CE25178013.pdf","label":"IPSJ-CE25178013.pdf"},"date":[{"dateType":"Available","dateValue":"2027-02-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CE25178013.pdf","filesize":[{"value":"1.4 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":"19"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"927f4434-9be0-4afc-b0c9-cc7d7d3ff11c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"隅谷,孝洋"}]},{"creatorNames":[{"creatorName":"天野,由貴"}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takahiro Sumiya","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yuki Amano","creatorNameLang":"en"}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10096193","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":"2188-8930","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"テキスト生成AIで、曖昧な自由記述文を「機械的に」分類したりラベル付けすることが可能になった。アンケート分析や対話分析など、この機能は広範囲にわたり便利に使うことができる。しかし、テキスト生成AIからの回答は「毎回違う」と言われることもあり、研究ツールとして使うためにはその安定性の評価が必要だと考えられる。ここでは、文化庁が募った「AIと著作権に関する考え方について（素案）」に対するパブリックコメントの分析を題材として、いくつかの方法でラベル付をした場合の安定性を評価する方法について考察する。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"With the advent of text-generative AI, it has become possible to “automatically” classify or label ambiguous free-form text. This capability can be very useful in a wide range of applications, such as survey analysis and dialogue analysis. However, because text-generating AI can produce different answers each time, it is considered necessary to evaluate its stability if we want to use it as a research tool. In this study, using the analysis of public comments submitted in response to the Agency for Cultural Affairs' “Draft Perspectives on AI and Copyright” as a case example, we explore methods for evaluating the stability of labeling when performed in several different ways.","subitem_description_type":"Other","subitem_description_language":"en"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータと教育（CE）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2025-02-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13","bibliographicVolumeNumber":"2025-CE-178"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"created":"2025-02-17T04:57:13.283209+00:00","id":2000313,"links":{}}