{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00199302","sets":["1164:5251:9700:9902"]},"path":["9902"],"owner":"44499","recid":"199302","title":["災害情報のリツイート傾向に基づいたアクティブユーザのグループ化と評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-09-12"},"_buckets":{"deposit":"c9e097d2-e081-48b2-9ec5-93d54938aab0"},"_deposit":{"id":"199302","pid":{"type":"depid","value":"199302","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"災害情報のリツイート傾向に基づいたアクティブユーザのグループ化と評価","author_link":["482172","482174","482173","482171"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"災害情報のリツイート傾向に基づいたアクティブユーザのグループ化と評価"},{"subitem_title":"Clustering and its Evaluation of Active Users based on the Retweet pattern of the disaster information on Twitter","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"地理空間サービスとアプリケーション","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2019-09-12","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"金沢工業大学"},{"subitem_text_value":"金沢工業大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kanazawa Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Kanazawa Institute of Technology","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/199302/files/IPSJ-EIP19085009.pdf","label":"IPSJ-EIP19085009.pdf"},"date":[{"dateType":"Available","dateValue":"2021-09-12"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-EIP19085009.pdf","filesize":[{"value":"1.2 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":"26"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"1613007f-c2ac-4767-b9a3-c2ad5ce66398","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐藤, 洸太朗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"阿部, 倫之"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kotaro, Sato","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Noriyuki, Abe","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11238429","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":"2188-8647","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から発信される災害情報の活用が進んでいる．ツイートを利用した災害情報の共有システムとしては，NICT の DISAANA が運用されており，自治体の防災担当者等が被災者のツイートを迅速に確認できる仕組みを提供している．ここで，被災者に近いフォロワーが少数の場合には初期段階においてツイートの拡散力が弱く，twitter 内において災害情報が共有されるまでには時間がかかる．また，支援者からのツイートはスクープ性が低いため，一般に拡散されにくい．そこで，過去の震災等において災害情報の拡散に貢献したアクティブユーザを把握できれば，リプライ等によって災害情報の迅速な拡散を促すことができる．本稿では，リツイート傾向の類似性に基づいてアクティブユーザをグループ化し，グループごとに被災ツイートの緊急性等を判定する手法を提案する．また，2018 年度に投稿された災害関連ツイートを用いて提案手法の評価を実施したので報告する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告電子化知的財産・社会基盤（EIP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-09-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"9","bibliographicVolumeNumber":"2019-EIP-85"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":199302,"updated":"2025-01-19T21:45:32.369867+00:00","links":{},"created":"2025-01-19T01:03:17.975298+00:00"}