Time Trend Analysis of “#Rescue” Tweets During and After The 2017 Northern Kyushu Heavy Rain Disaster

机译：“#RESCUE”推文和2017年北九州大雨灾害期间和之后的时间趋势分析

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In Japan, when a large-scale natural disaster occurs, numerous messages (i.e., “tweets”) related to the disaster are posted on Twitter. Victims who need to be rescued use the hashtag (meaning #Rescue) on the tweets to request a rescue. The effectiveness of tweets with this kind of hashtag has been discussed in several papers. In this paper, we collect and analyze tweets with the hashtag #Rescue posted during and after the 2017 Northern Kyushu Heavy Rain Disaster. We also investigate the time trend of the tweet contents that has not been examined in previous papers.

机译：在日本，当发生大规模的自然灾害时，与灾难有关的大量消息（即“推文”）在Twitter上发布。需要救出的受害者使用推文上的Hashtag（意思是#rescue）来申请救援。在几篇论文中讨论了Tweets与这种哈希特的有效性。在本文中，我们在2017年北部北部九州大雨灾难期间和之后收集和分析推文#Rescue。我们还调查了在前论文中尚未审查的推文内容的时间趋势。

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《International Conference on Information and Communication Technologies for Disaster Management》|2019年|170p|共4页
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Shuji Nishikawa; Nozomi Tanaka; Keisuke Utsu; Osamu Uchida;
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正文语种
中图分类通信;
关键词
Twitter; Rain; Tagging; Histograms; Market research; Urban areas;

机译：Twitter;雨;标记;直方图;市场研究;城市地区;

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1. Examination of Sediment Dynamics Based on the Distribution of Silica Fluxes and Flood Sediments in the Otoishi River Related to the Northern Kyushu Heavy Rain Disaster, July 2017 [J] . Ryunosuke Nakanishi, Akira Baba, Takahiro Tsuyama, Geosciences . 2019,第2期

机译：2017年7月，根据与九州北部暴雨灾害相关的大石江的硅通量和洪水沉积物分布调查沉积物动力学
2. Contrasting Features of the July 2018 Heavy Rainfall Event and the 2017 Northern Kyushu Rainfall Event in Japan [J] . Hiroki TSUJI, Chie YOKOYAMA, Yukari N. TAKAYABU ournal of the Meteorological Society of Japan . 2020,第4期

机译：2018年7月的对比特点大雨事件和2017年日本北九州北部的降雨活动
3. ANALYSIS OF HEAVY RAIN FROM TYPHOON NUMBER 3 (2017) USING X-BAND MULTIPARAMETER RADAR DATA, KYUSHU, JAPAN [J] . Nishio M., Mori M. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences . 2018,第4期

机译：利用日本九州的X波段多参数雷达数据对台风3号（2017年）的大雨进行分析
4. Time Trend Analysis of “#Rescue” Tweets During and After The 2017 Northern Kyushu Heavy Rain Disaster [C] . Shuji Nishikawa, Nozomi Tanaka, Keisuke Utsu, International Conference on Information and Communication Technologies for Disaster Management . 2019

机译：“#RESCUE”推文和2017年北九州大雨灾害期间和之后的时间趋势分析
5. Sentiment Analysis on Tweets and their Relationship with Stock Market Trends. [D] . Sharma, Jay. 2013

机译：关于推文的情感分析及其与股市趋势的关系。
6. Analysis of the Actions and Motivations of a Community during the 2017 Torrential Rains in Northern Kyushu Japan [O] . Atsuko Nonomura, Kazuhito Fujisawa, Mari Takahashi, 2020

机译：日本北部九州2017年特大暴雨期间社区的行动和动机分析
7. Examination of Sediment Dynamics Based on the Distribution of Silica Fluxes and Flood Sediments in the Otoishi River Related to the Northern Kyushu Heavy Rain Disaster, July 2017 [O] . Ryunosuke Nakanishi, Akira Baba, Takahiro Tsuyama, 2019

机译：基于北九州河河河河河河河河河河河河散沉沉积物分布的沉积物动力学研究，2017年7月

Time Trend Analysis of “#Rescue” Tweets During and After The 2017 Northern Kyushu Heavy Rain Disaster

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