{"_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"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/6583", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2024-05-20"}, "publish_date": "2024-05-20", "publish_status": "0", "recid": "6583", "relation": {}, "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_shared_id": -1}