{"created":"2025-01-19T01:45:16.190493+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240846","sets":["6164:6165:6462:11854"]},"path":["11854"],"owner":"11","recid":"240846","title":["X上のBot判別モデルの提案およびBotアカウントの特徴に関する考察"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-10-15"},"_buckets":{"deposit":"29913d11-c53b-4a69-888f-9178ad30e32a"},"_deposit":{"id":"240846","pid":{"type":"depid","value":"240846","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"X上のBot判別モデルの提案およびBotアカウントの特徴に関する考察","author_link":["661711","661712","661713","661714","661715","661716"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"X上のBot判別モデルの提案およびBotアカウントの特徴に関する考察","subitem_title_language":"ja"},{"subitem_title":"A Proposal of Bot Detection Model on X and Consideration of Bot Account Characteristics","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソーシャルメディア，ソーシャルボット，Twitter，X，Bot 判別","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-10-15","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"明治大学大学院"},{"subitem_text_value":"明治大学"},{"subitem_text_value":"明治大学／レンジフォース株式会社"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Meiji University / Rangeforce, Inc.","subitem_text_language":"en"}]},"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/240846/files/IPSJ-CSS2024100.pdf","label":"IPSJ-CSS2024100.pdf"},"date":[{"dateType":"Available","dateValue":"2026-10-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSS2024100.pdf","filesize":[{"value":"383.7 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"50b60a59-d739-425a-bf52-034dc8643734","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"多川, 哲史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小玉, 直樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"齋藤, 孝道"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Satoshi, Tagawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Naoki, Kodama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takamichi, Saito","creatorNameLang":"en"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ソーシャルネットワーキングサービス(SNS)の1つであるX(旧Twitter)は，情報発信や共有において重要な役割を果たしている．しかし，SNS上での世論操作や社会的混乱を引き起こそうとする試みも増加している．2016年の米国大統領選挙において，X上でBotを利用した工作行為が確認されている．本論文では，Bot判別モデルの開発に向けて，複数の回帰分析アルゴリズムとデータセットの前処理の精度比較を行った．その結果，正解ラベル均一化を施したデータセットを用いてRandomForestRegressorを学習させたモデルが有効であった．さらに，政治系と比較用の複数のデータセットに対して，作成したBot判別モデルを適用した．その結果，比較用データセットに比べて政治系のデータセットは，Botアカウントの割合が高い結果となった．また，政治系の話題ではBotアカウントがリポストを通じて情報を拡散させる傾向があった．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"X (formerly Twitter), a social networking service (SNS), plays an important role in disseminating and sharing information. However, attempts to manipulate public opinion and cause social disruption on SNS are also increasing. In the 2016 U.S. presidential election, manipulation using Bots on X has been confirmed. In this paper, we compare the accuracy of several regression analysis algorithms and pre-processing of datasets to develop a Bot discriminant model. The results showed that the model trained with RandomForestRegressor using a dataset with homogenized correct answers labels was effective. In addition, we applied the Bots discriminant model to several datasets, one for political systems and another for comparison. The results showed that the political dataset had a higher percentage of bot accounts than the comparison dataset. Bot accounts tended to spread information on political topics through reposts. ","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"742","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2024論文集"}],"bibliographicPageStart":"735","bibliographicIssueDates":{"bibliographicIssueDate":"2024-10-15","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":240846,"updated":"2025-03-06T05:34:06.030712+00:00","links":{}}