{"created":"2025-11-13T02:08:09.087199+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02005697","sets":["1164:3368:11904:1761809989445"]},"path":["1761809989445"],"owner":"80578","recid":"2005697","title":["不真面目回答に対するLLMを活用したナッジ介入の効果の検討：クラウドソーシングを用いて"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-11-29"},"_buckets":{"deposit":"54bccf0e-8764-4fca-aaf4-4f1e16a1ca4c"},"_deposit":{"id":"2005697","pid":{"type":"depid","value":"2005697","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"不真面目回答に対するLLMを活用したナッジ介入の効果の検討：クラウドソーシングを用いて","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"不真面目回答に対するLLMを活用したナッジ介入の効果の検討：クラウドソーシングを用いて","subitem_title_language":"ja"},{"subitem_title":"Evaluating the Effectiveness of LLM-Based Nudge Interventions to Reduce Insufficient Effort Responses: Evidence from a Crowdsourcing Platform","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2025-11-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"明治大学"},{"subitem_text_value":"明治大学"}]},"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/2005697/files/IPSJ-IS25174006.pdf","label":"IPSJ-IS25174006.pdf"},"date":[{"dateType":"Available","dateValue":"2027-11-29"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IS25174006.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":"38"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"89d94612-8dea-480e-97c1-43d9055e8206","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":"生井沢,祥吾"}]},{"creatorNames":[{"creatorName":"後藤,晶"}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shogo Namaisawa","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Akira Goto","creatorNameLang":"en"}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11253943","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":"2188-8809","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究は，クラウドソーシングによるアンケート調査において，努力最小化（satisfice）により生じる不真面目回答の抑制を目的とし，ナッジ介入の効果を検証するものである．従来から用いられてきた事前申告や利得強調，損失回避型の手法に加え，大規模言語モデル（LLM）により生成されたナッジメッセージが回答品質の向上に寄与するかを，アンケート回答者をランダムに振り分けて比較する平均処置効果（ATE）によって検証した．その結果，利得強調や損失回避による介入で抑制させる傾向がみられたものの，すべての介入群で統計的に有意な抑制効果は見られなかった．このことから，ナッジ介入の効果がないということを強く示唆するものではなく，不真面目回答に対する効果は存在したとしても小さな効果量であることが考えられる．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This study examines whether nudge interventions can mitigate insufficient effort responses arising from effort minimization (satisficing) on a crowdsourcing platform. In addition to established approaches―pre-commitment, gain framing, and loss framing―we evaluate whether nudge messages generated by large language models (LLMs) improve response quality. We estimate average treatment effect (ATE) by randomly assigning survey participants to experimental conditions and comparing outcomes. The results indicated that while the gain-framing and loss-framing interventions showed a tendency to suppress these responses, no statistically significant suppression effect was observed in any of the intervention groups. This suggests that if an effect on insufficient effort responses exists, it is likely of a small magnitude, and that the sample size of this study was insufficient to detect it as a statistically significant difference.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告情報システムと社会環境（IS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2025-11-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2025-IS-174"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"id":2005697,"updated":"2025-11-13T02:18:36.334845+00:00","links":{}}