Qu Zheng, Wang Juanle, Zhang Min
School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, Shandong, China.
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Heliyon. 2023 Jul 14;9(7):e18272. doi: 10.1016/j.heliyon.2023.e18272. eCollection 2023 Jul.
Cities are concentrated areas of population that are vulnerable to the impact of natural disasters. Owing to the impact of climate change and extreme weather incidents in recent years, many cities worldwide have been affected by sudden disasters, especially floods, causing many casualties. Social media plays an important role in the communication and sharing of information when physical communication is limited in emergency situations. However, obtaining and using public sentiment during major disasters to provide support for emergency disaster relief is a popular research topic. In the summer of 2021, China's inland plains experienced extremely serious rainstorms. The rainfall on July 20 in the capital city of Zhengzhou, Henan Province, the most population province in China, reached 201.9 mm/h, causing extremely serious consequences. This case study examines people's sentiment about this event through datamining of Chinese Weibo social media during the extreme rainfall period. The six most concerned types of public response topics and 14 subcategory topics were determined from 2,124,162 Weibo messages. "Asking for help" and "public sentiment" dominated the main topics, reaching almost 66%, with a relatively even distribution of secondary categories, but with "appeal for assistance" taking the top spot. Topics changed cyclically with work and rest, but these areas seemed to lag behind coastal areas in their responses to the storm in the same time. The topics were centred around Zhengzhou and distributed in China's major city clusters, such as the Beijing-Tianjin-Hebei agglomerations, Yangtze River Delta, and Pearl River Delta regions. Community-level disaster relief information was also discovered, which showed that high building power outages, basement flooding, tunnel trapping, and drinking water shortages were common topics in specific inner urban regions. This detailed information will contribute to accurate location-based relief in the future. Based on this lesson, a series of measures for urban flood reduction are proposed, including disaster prevention awareness, infrastructure building, regulation mechanisms, social inclusivity, and media dissemination.
城市是人口密集地区，容易受到自然灾害的影响。由于近年来气候变化和极端天气事件的影响，全球许多城市都受到突发灾害的影响，尤其是洪水，造成了许多人员伤亡。在紧急情况下，当实体交流受限，社交媒体在信息传播和共享中发挥着重要作用。然而，在重大灾害期间获取并利用公众情绪为紧急救灾提供支持是一个热门研究课题。2021年夏天，中国内陆平原遭遇了极其严重的暴雨。7月20日，中国人口最多的省份河南省省会郑州的降雨量达到201.9毫米/小时，造成了极其严重的后果。本案例研究通过对极端降雨期间中国微博社交媒体的数据挖掘，考察了人们对这一事件的情绪。从2124162条微博信息中确定了最受关注的六种公众反应话题类型和14个子类别话题。“求助”和“公众情绪”在主要话题中占主导地位，几乎达到66%，二级类别分布相对均匀，但“寻求援助”位居榜首。话题随作息时间呈周期性变化，但这些地区在同一时间对风暴的反应似乎落后于沿海地区。话题以郑州为中心，分布在中国的主要城市群，如京津冀城市群、长江三角洲和珠江三角洲地区。还发现了社区层面的救灾信息，表明高层建筑停电、地下室洪水、隧道被困和饮用水短缺是特定城市内部区域的常见话题。这些详细信息将有助于未来基于位置的精准救灾。基于此教训，提出了一系列城市防洪措施，包括防灾意识、基础设施建设、监管机制、社会包容性和媒体传播。
