{"updated":"2025-01-20T02:07:17.013179+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00187707","sets":["6504:9465:9471"]},"path":["9471"],"owner":"6748","recid":"187707","title":["小規模構成で実施可能な大量ツイート分析手法の提案(1) ― 「バルス」ツイートを対象とした収集方法検証"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-03-13"},"_buckets":{"deposit":"17378be9-8f58-428f-b41f-79f3b04775c5"},"_deposit":{"id":"187707","pid":{"type":"depid","value":"187707","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"小規模構成で実施可能な大量ツイート分析手法の提案(1) ― 「バルス」ツイートを対象とした収集方法検証","author_link":["425209","425208","425210"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"小規模構成で実施可能な大量ツイート分析手法の提案(1) ― 「バルス」ツイートを対象とした収集方法検証"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データとウェブ","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2018-03-13","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"USP研"},{"subitem_text_value":"USP研"},{"subitem_text_value":"金沢大"}]},"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/187707/files/IPSJ-Z80-4B-02.pdf","label":"IPSJ-Z80-4B-02.pdf"},"date":[{"dateType":"Available","dateValue":"2018-04-25"}],"format":"application/pdf","filename":"IPSJ-Z80-4B-02.pdf","filesize":[{"value":"506.2 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"666f9514-dad6-4cf2-a81c-12fa37642426","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松浦, 智之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"當仲, 寛哲"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大野, 浩之"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ツイッター分析は、ニュース番組でも頻繁に用いられるなど、その需要は増加している。しかしその手法を調査しても、大企業等が大きな予算や設備を導入して行う事例が殆どであり、個人の例は殆ど報告されていない。本研究では個人等がコンピュータ1台で行える手法を研究した。第1報では、本手法の概要及び、分析の前段階であるツイート収集方法を説明する。重要なことは、世界の全ツイートの収集を目指すのではなく、目的の分析テーマに応じて適切なクエリを発行し、受信するツイートを絞り込む点にある。本手法の有効性検証のため、Twitter社のサービスを停止させる程に大量に発生する「バルス」ツイートを収集し、NTTデータ社の収集結果と比較する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"360","bibliographic_titles":[{"bibliographic_title":"第80回全国大会講演論文集"}],"bibliographicPageStart":"359","bibliographicIssueDates":{"bibliographicIssueDate":"2018-03-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2018"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T00:54:21.706137+00:00","id":187707,"links":{}}