{"created":"2023-05-15T08:43:56.419604+00:00","id":9095,"links":{},"metadata":{"_buckets":{"deposit":"5de61376-3bb3-4c40-adb6-280b17f35d84"},"_deposit":{"created_by":13,"id":"9095","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"9095"},"status":"published"},"_oai":{"id":"oai:uec.repo.nii.ac.jp:00009095","sets":["6"]},"author_link":["24667","8598","24771","24288","24289","24290"],"control_number":"9095","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2013-12-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"12","bibliographicPageEnd":"2999","bibliographicPageStart":"2987","bibliographicVolumeNumber":"J96-D","bibliographic_titles":[{"bibliographic_title":"電子情報通信学会論文誌. D, 情報・システム","bibliographic_titleLang":"ja"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"昨今，インターネットの普及などから様々な情報源（ソーシャルメディア・マスメディア）に容易にアクセスし，多様な意見・考え方に触れることが可能になった．同時に，ソーシャルメディアにおけるデマの拡散や，マスメディアにおける偏向報道・情報操作の疑いなど，ユーザ自身が情報の信頼性について自ら判断することが求められてきている．そこで我々は，一般ユーザがメディア情報を多角的な観点から比較することを支援するため，ユーザに代わってソーシャル，マス両メディアから特定の話題に関する情報を抽出，見える化し，特定の観点に基づく比較ポイントを提示するエージェントシステムを目指している．本論文では，Conditional Random Fieldsと事象抽出のためのヒューリスティクスを用いて，Twitter上のツイート，マスメディアのニュース記事等から13の属性情報をもつ事象情報を抽出し，それらをLinked Data化する手法を提案し，精度評価を行った．また，事例を通して多様性，希少性，偏在性，因果関係の四つの観点に沿って比較ポイントを抽出することで有用性を確認した．","subitem_description_type":"Abstract"},{"subitem_description":"Growth of Internet makes easy access to several information sources such as social and mass media, and then truly diverse attitudes and opinions these day. At the same time, users are required to judge the information credibility due to spreading of false rumor in the social media and suspicion of biased coverage in the mass media. Thus, in order to support the comparison of media information from several aspects, we are aiming at an agent system which extracts and visualizes the information of a certain event from both medias, and then presents some points to be compared. This paper proposes a method to extract the event information with 13 attributes from tweets and news articles using Conditional Random Fields and heuristic rules, and convert it to Linked Data, and then evaluates its extraction accuracy. Moreover, it confirmed the usefulness though case studies by extracting comparable points from four aspects of diversity, infrequency, uneven distribution, causal association.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"電子情報通信学会"}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://search.ieice.org/index.html","subitem_relation_type_select":"URI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"Copyright © 2014 IEICE"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1881-0225","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"川村, 隆浩","creatorNameLang":"ja"},{"creatorName":"カワムラ, タカヒロ","creatorNameLang":"ja-Kana"},{"creatorName":"Kawamura, Takahiro","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"越川, 兼地","creatorNameLang":"ja"},{"creatorName":"コシカワ, ケンジ","creatorNameLang":"ja-Kana"},{"creatorName":"KOSHIKAWA, Kenji","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中川, 博之","creatorNameLang":"ja"},{"creatorName":"ナカガワ, ヒロユキ","creatorNameLang":"ja-Kana"},{"creatorName":"NAKAGAWA, Hiroyuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"清, 雄一","creatorNameLang":"ja"},{"creatorName":"セイ, ユウイチ","creatorNameLang":"ja-Kana"},{"creatorName":"SEI, Yuichi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田原, 康之","creatorNameLang":"ja"},{"creatorName":"タハラ, ヤスユキ","creatorNameLang":"ja-Kana"},{"creatorName":"TAHARA, Yasuyuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大須賀, 昭彦","creatorNameLang":"ja"},{"creatorName":"オオスガ, アキヒコ","creatorNameLang":"ja-Kana"},{"creatorName":"OHSUGA, Akihiko","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-04-09"}],"displaytype":"detail","filename":"j96-d_12_2987.pdf","filesize":[{"value":"3.7 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"j96-d_12_2987","url":"https://uec.repo.nii.ac.jp/record/9095/files/j96-d_12_2987.pdf"},"version_id":"9a7502ee-928f-40ff-b9e4-b0d630379184"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"エージェント","subitem_subject_scheme":"Other"},{"subitem_subject":"Linked Data","subitem_subject_scheme":"Other"},{"subitem_subject":"メディア比較","subitem_subject_scheme":"Other"},{"subitem_subject":"agent","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"linked data","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"social-vs-mass media","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"メディア情報のLinked Data化と活用事例の提案","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"メディア情報のLinked Data化と活用事例の提案","subitem_title_language":"ja"},{"subitem_title":"Proposal of Social-Mass Media Triplification and Its Use Case","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"13","path":["6"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2019-04-09"},"publish_date":"2019-04-09","publish_status":"0","recid":"9095","relation_version_is_last":true,"title":["メディア情報のLinked Data化と活用事例の提案"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2024-03-04T02:40:48.491128+00:00"}