{"created":"2024-04-15T01:14:41.859889+00:00","id":6583,"links":{},"metadata":{"_buckets":{"deposit":"164975eb-3fd8-407d-b15b-da5da41f565f"},"_deposit":{"created_by":10,"id":"6583","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"6583"},"status":"published"},"_oai":{"id":"oai:nied-repo.bosai.go.jp:00006583","sets":[]},"author_link":[],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-10-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicPageEnd":"955","bibliographicPageStart":"944","bibliographicVolumeNumber":"17","bibliographic_titles":[{"bibliographic_title":"Journal of Disaster Research","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"To carry out natural disaster response, restoration, and reconstruction, it is important to efficiently and quickly assess the damage caused by the natural disaster. The existing evidence demonstrates that when a natural disaster occurs, social networking services (SNS) information is amplified significantly, compared to normal times. Specifically, the damage caused by a natural disaster tends to cover a wide area and have a large scale. Additionally, it may vary considerably depending on the municipality. Thus, this study investigates whether the utilization of this amplified SNS information can offer an effective approach for real-time evaluation and monitoring of the damage caused by a natural disaster in municipal units. To this end, focusing on time-series changes in SNS information, we propose a general-purpose analysis method of SNS information for evaluating the damage caused by a natural disaster in real time in municipal units. Using real-world data twitter data, we investigate the case of Kumamoto Prefecture, which experienced heavy rain in July 2020 and July 2021, to verify the proposed analysis method.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Fuji Technology Press Ltd.","subitem_publisher_language":"en"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"10.20965/jdr.2022.p0944"}}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1883-8030","subitem_source_identifier_type":"EISSN"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Cui Qinglin","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Shoyama Kikuko","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Hanashima Makoto","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Usuda Yuichiro","creatorNameLang":"en"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_title":"Early Estimation of Heavy Rain Damage at the Municipal Level Based on Time-Series Analysis of SNS Information","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Early Estimation of Heavy Rain Damage at the Municipal Level Based on Time-Series Analysis of SNS Information","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"10","path":["1670839190650"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-05-20"},"publish_date":"2024-05-20","publish_status":"0","recid":"6583","relation_version_is_last":true,"title":["Early Estimation of Heavy Rain Damage at the Municipal Level Based on Time-Series Analysis of SNS Information"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2024-05-21T04:06:04.229361+00:00"}