{"created":"2023-06-20T16:51:10.243272+00:00","id":23828,"links":{},"metadata":{"_buckets":{"deposit":"84e804b5-c5ee-42c9-9d23-e4bb6ca23932"},"_deposit":{"created_by":3,"id":"23828","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"23828"},"status":"published"},"_oai":{"id":"oai:kindai.repo.nii.ac.jp:00023828","sets":["14:923:1081:4856"]},"author_link":["44447"],"item_2_biblio_info_21":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2023-03-31","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicPageEnd":"179","bibliographicPageStart":"169","bibliographicVolumeNumber":"69","bibliographic_titles":[{"bibliographic_title":"商経学叢"},{"bibliographic_title":"Shokei-gakuso: Journal of Business Studies","bibliographic_titleLang":"en"}]}]},"item_2_description_33":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"[概要]本研究では航空会社に関する口コミや満足度について，統計分析，テキストマイニング，機械学習，BERT等のデータ解析を行う。対象とするデ－タは２つあり，(1) 国立情報学研究所のIDRデータセット提供サービスにより株式会社マイスタースタジオから提供を受けた「みんなの評判口コミデータセット」と(2)国立情報学研究所のIDRデータセット提供サービスにより株式会社oricon MEから提供を受けた「オリコンデータセット」である。「みんなの評判口コミデータセット」について行った分析は以下の通りである。口コミに関しては，トピックモデルのLDAにより，予約の変更，会社の対応，コロナによるキャンセルに関する対応，空港における搭乗時の荷物に関する対応に分類された。満足度に関して順序プロビットモデルによって統計的に満足度を推計した。教師あり機械学習（SVM，ニューラルネットワーク，ランダムフォレスト）， BERT（Bidirectional Encoder Representations from Transformers）で順序プロビットモデルで構築したモデルについて評価を行った。BERTの場合のaccuracy scoreがもっとも高い結果となった。「オリコンデータセット」を用いて行ったことは，格安航空券LCCの満足度に関して順序プロビットモデルで分析した結果，ホスピタリティ要因の重要性が確認できた。\n[Abstract] This paper conducts statistical analysis, text mining, machine learning, and BERT (Bidirectional Encoder Representations from Transformers) to the WOM related to airlines. The datasets that this paper analyzes are (1) \"Minhyo Review Dataset\" provided by meisterstudio, Inc. via IDR Dataset Service of National Institute of Informatics, (2) \"Oricon Dataset\" provided by oricon ME Inc., via IDR Dataset Service of National Institute of Informatics. First, the data analysis of \"Minhyo Review Dataset\" classified the WOM of change reservation, company correspondence, correspondence to the cancellation due to COVID-19, and correspondence to baggage when boarding by LDA, which is one of the topic models. The satisfaction of the airlines was estimated by the ordered probit model. Supervised learning (SVM (Support Vector Machine), neural network, random forest) and BERT (Bidirectional Encoder Representations from Transformers) accessed the result from the ordered probit model. Second, estimating the satisfaction of LCC by the ordered probit model using \"Oricon Dataset\" confirmed the importance of the hospitality factor.","subitem_description_type":"Abstract"}]},"item_2_description_41":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_2_publisher_14":{"attribute_name":"出版者 名前","attribute_value_mlt":[{"subitem_publisher":"近畿大学商経学会"}]},"item_2_source_id_22":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"04502825","subitem_source_identifier_type":"ISSN"}]},"item_2_text_7":{"attribute_name":"著者(英)","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Minetaki, Kazunori"}]},"item_2_text_8":{"attribute_name":"著者 所属","attribute_value_mlt":[{"subitem_text_value":"近畿大学経営学部; 教授"}]},"item_2_text_9":{"attribute_name":"著者所属(翻訳)","attribute_value_mlt":[{"subitem_text_value":"Kindai University"}]},"item_2_version_type_12":{"attribute_name":"版","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_be7fb7dd8ff6fe43","subitem_version_type":"NA"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"峰滝, 和典"},{"creatorName":"ミネタキ, カズノリ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"44447","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2023-03-23"}],"displaytype":"detail","filename":"AN10437975-20230331-0169.pdf","filesize":[{"value":"960.7 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"AN10437975-20230331-0169.pdf","url":"https://kindai.repo.nii.ac.jp/record/23828/files/AN10437975-20230331-0169.pdf"},"version_id":"b014f248-9e48-4fed-aef1-abc6f5870e4a"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"順序プロビットモデル","subitem_subject_scheme":"Other"},{"subitem_subject":"機械学習","subitem_subject_scheme":"Other"},{"subitem_subject":"SVM","subitem_subject_scheme":"Other"},{"subitem_subject":"ニューラルネットワーク","subitem_subject_scheme":"Other"},{"subitem_subject":"ランダムフォレスト","subitem_subject_scheme":"Other"},{"subitem_subject":"BERT","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":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"航空会社の口コミと満足度に関するデータ解析","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"航空会社の口コミと満足度に関するデータ解析"},{"subitem_title":"Data Analysis of of WOM and Customer Satisfaction of Airline Companies","subitem_title_language":"en"}]},"item_type_id":"2","owner":"3","path":["4856"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-03-23"},"publish_date":"2023-03-23","publish_status":"0","recid":"23828","relation_version_is_last":true,"title":["航空会社の口コミと満足度に関するデータ解析"],"weko_creator_id":"3","weko_shared_id":3},"updated":"2023-06-20T19:04:58.414967+00:00"}